{"cells":[{"metadata":{},"cell_type":"markdown","source":"![https://storage.googleapis.com/kaggle-competitions/kaggle/22420/logos/header.png?t=2020-09-08-21-21-20](https://storage.googleapis.com/kaggle-competitions/kaggle/22420/logos/header.png?t=2020-09-08-21-21-20)"},{"metadata":{},"cell_type":"markdown","source":"CDP is a global non-profit that drives companies and governments to reduce their greenhouse gas emissions, safeguard water resources, and protect forests. Each year, CDP takes the information supplied in its annual reporting process and scores companies and cities based on their journey through disclosure and towards environmental leadership.\n\nCDP houses the world’s largest, most comprehensive dataset on environmental action. As the data grows to include thousands more companies and cities each year, there is increasing potential for the data to be utilized in impactful ways. Because of this potential, CDP is excited to launch an analytics challenge for the Kaggle community. Data scientists will scour environmental information provided to CDP by disclosing companies and cities, searching for solutions to our most pressing problems related to climate change, water security, deforestation, and social inequity.\n\n* How do you help cities adapt to a rapidly changing climate amidst a global pandemic, but do it in a way that is socially equitable?\n\n* What are the projects that can be invested in that will help pull cities out of a recession, mitigate climate issues, but not perpetuate racial/social inequities?\n\n* What are the practical and actionable points where city and corporate ambition join, i.e. where do cities have problems that corporations affected by those problems could solve, and vice versa?\n\n* How can we measure the intersection between environmental risks and social equity, as a contributor to resiliency?"},{"metadata":{},"cell_type":"markdown","source":"Overview of the Data:\n\nThe CDP dataset consists of publicly available responses to 3 different surveys: (1) corporate climate change disclosures; (2) corporate water security disclosures; and (3) disclosures from cities. Data is available for 2018, 2019, and 2020, along with a small collection of supplementary datasets. A starter notebook demonstrates how to load and work with the data.\n\nMain Data:\n* 2018_Full_Climate_Change_Dataset.csv (298.53 MB)\n* 2019_Full_Climate_Change_Dataset.csv (879.62 MB)\n* 2020_Full_Climate_Change_Dataset.csv (511.43 MB)\n* 2018_Full_Water_Security_Dataset.csv (64.52 MB)\n* 2019_Full_Water_Security_Dataset.csv (128.6 MB)\n* 2020_Full_Water_Security_Dataset.csv(127.32 MB)\n* 2018_Full_Cities_Dataset.csv (71.16 MB)\n* 2019_Full_Cities_Dataset.csv (214.66 MB)\n* 2020_Full_Cities_Dataset.csv (365.1 MB)"},{"metadata":{},"cell_type":"markdown","source":"![https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1314380%2F6f0f4d334e5b094bfcf002c4d2e931f6%2FCDP_dataset.png?generation=1603468553539656&alt=media](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1314380%2F6f0f4d334e5b094bfcf002c4d2e931f6%2FCDP_dataset.png?generation=1603468553539656&alt=media)"},{"metadata":{},"cell_type":"markdown","source":"See Detailed :https://www.kaggle.com/c/cdp-unlocking-climate-solutions/data"},{"metadata":{},"cell_type":"markdown","source":"# Ok Let's Visualize the data"},{"metadata":{},"cell_type":"markdown","source":"Import Library"},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"import numpy as np\nimport pylab as pl\nimport pandas as pd\nimport matplotlib.pyplot as plt \n%matplotlib inline\nimport wordcloud\nfrom wordcloud import WordCloud,STOPWORDS\nimport seaborn as sns\nfrom wordcloud import WordCloud, STOPWORDS, ImageColorGenerator\nfrom sklearn.utils import shuffle\nfrom sklearn.svm import SVC\nfrom sklearn.metrics import confusion_matrix,classification_report\nfrom sklearn.model_selection import cross_val_score, GridSearchCV\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Read Dataset"},{"metadata":{},"cell_type":"markdown","source":"# Cities Disclosing"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_2018 = pd.read_csv('../input/cdp-unlocking-climate-solutions/Cities/Cities Disclosing/2018_Cities_Disclosing_to_CDP.csv')\nCities_2019 = pd.read_csv('../input/cdp-unlocking-climate-solutions/Cities/Cities Disclosing/2019_Cities_Disclosing_to_CDP.csv')\nCities_2020 = pd.read_csv('../input/cdp-unlocking-climate-solutions/Cities/Cities Disclosing/2020_Cities_Disclosing_to_CDP.csv')\n\n\nData= Cities_2018.append([Cities_2018,Cities_2019, Cities_2020])\nx = Data.iloc[:, [3]].values","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Data.head()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Population"},{"metadata":{},"cell_type":"markdown","source":"### Here we are comparing the Population with each Country, first group the Country and get max,min and avg (mean) of Population"},{"metadata":{"trusted":true},"cell_type":"code","source":"\ndisplay(Data[[\"Country\",\"Population\",]].groupby([\"Country\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Data['Account_Number'] = Data['Account Number']\nData['Population_Year'] = Data['Population Year']\nData['Reporting_Authority'] = Data['Reporting Authority']\n\nData","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Population by time series \n"},{"metadata":{"trusted":true},"cell_type":"code","source":"#Data['Population_Year'] = Data[\"Population_Year\"].astype(\"int\")\n#print('population by time series ')\ndisplay(Data[[\"Population_Year\",'Country','City','Population','Reporting_Authority']].groupby([\"Country\",\"City\",\n                                                        \"Population_Year\", ]).agg(\"sum\").sort_values(by=\"Population\",\n                                                          ascending = False).head(100).style.background_gradient(cmap='autumn'))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Population distribution"},{"metadata":{"trusted":true},"cell_type":"code","source":"# Plot Population distribution\nfig, axes = plt.subplots(nrows=1, ncols=3, figsize=(15,4))\nplt.subplots_adjust(wspace=0.5, hspace=0.5)\n\nsns.distplot(Data.Population[(Data.Population>=0) & (Data.Population<=10000)], kde=False, ax=axes[0], axlabel='Population')\nsns.distplot(Data.Population[(Data.Population>=0) & (Data.Population<=100000)], kde=False, ax=axes[1], axlabel='Population')\nsns.distplot(Data.Population[(Data.Population>=0) & (Data.Population<=1000000)], kde=False, ax=axes[2], axlabel='Population')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Population by Account_Number"},{"metadata":{"trusted":true},"cell_type":"code","source":"population_1 = Data.sort_values(by='Account_Number', ascending=True)[:100]\nfigure = plt.figure(figsize=(10,6))\nsns.barplot(y=population_1.Country, x=population_1.Account_Number)\nplt.xticks(rotation=90)\nplt.xlabel('Account_Number')\nplt.ylabel('Population ')\nplt.title('Population by Account_Number')\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Country Population"},{"metadata":{"trusted":true},"cell_type":"code","source":"population = Data.sort_values(by='Population', ascending=True)[:100]\nfigure = plt.figure(figsize=(10,6))\nsns.barplot(y=population.Country, x=population.Population)\nplt.xticks()\nplt.xlabel('Population')\nplt.ylabel('Country')\nplt.title('Country Population ')\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## City Population"},{"metadata":{"trusted":true},"cell_type":"code","source":"population = Data.sort_values(by='Population', ascending=True)[:100]\nfigure = plt.figure(figsize=(10,6))\nsns.barplot(y=population.City, x=population.Population)\nplt.xticks()\nplt.xlabel('Population')\nplt.ylabel('City')\nplt.title('City Population')\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"##  Year Reported to CDP"},{"metadata":{"trusted":true},"cell_type":"code","source":"Data['Year_Reported_to_CDP'] = Data['Year Reported to CDP']\nData['Account_Number'] = Data['Account Number']\nData","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"YR_CDP = Data['Year_Reported_to_CDP'].value_counts()  [:50]\nplt.figure(figsize=(6,4))\nsns.barplot(YR_CDP.index, YR_CDP.values, alpha=0.8)\nplt.ylabel('Number of Data', fontsize=12)\nplt.xlabel('Year_Reported_to_CDP', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"In the chart above, you can see in the far left 2018 of Year_Reported_to_CDP were higher that has the amount at least 1200"},{"metadata":{"trusted":true},"cell_type":"code","source":"population = Data.sort_values(by='Population', ascending=True)[:100]\nfigure = plt.figure(figsize=(10,6))\nsns.barplot(y=population.Year_Reported_to_CDP, x=population.Population)\nplt.xticks(rotation=90)\nplt.xlabel('Population')\nplt.ylabel('Year Reported to CDP')\nplt.title('Year Reported to CDP ')\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"##  Population Year"},{"metadata":{"trusted":true},"cell_type":"code","source":"population = Data.sort_values(by='Population', ascending=True)[:100]\nfigure = plt.figure(figsize=(10,6))\nsns.barplot(y=population.Population_Year, x=population.Population)\nplt.xticks(rotation=90)\nplt.xlabel('Population')\nplt.ylabel('Population_Year')\nplt.title('Population_Year ')\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"cdp = pd.read_csv('../input/cdp-unlocking-climate-solutions/Cities/Cities Disclosing/Cities_Disclosing_to_CDP_Data_Dictionary.csv')\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"cdp.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Start with one description:\ntext = cdp.description[1]\n\n# Create and generate a word cloud image:\nwordcloud = WordCloud().generate(text)\n\n# Display the generated image:\nplt.imshow(wordcloud, interpolation='bilinear')\nplt.axis(\"off\")\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# lower max_font_size, change the maximum number of word and lighten the background:\nwordcloud = WordCloud(max_font_size=50, max_words=100, background_color=\"white\").generate(text)\nplt.figure()\nplt.imshow(wordcloud, interpolation=\"bilinear\")\nplt.axis(\"off\")\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"text = \" \".join(review for review in cdp.description)\nprint (\"There are {} words in the CDP.\".format(len(text)))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Create stopword list:\nstopwords = set(STOPWORDS)\nstopwords.update([\"city\", \"population\", \"organisation\"])\n\n# Generate a word cloud image\nwordcloud = WordCloud(stopwords=stopwords, background_color=\"white\").generate(text)\n\n# Display the generated image:\n# the matplotlib way:\nplt.imshow(wordcloud, interpolation='bilinear')\nplt.axis(\"off\")\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Cities Responses"},{"metadata":{"trusted":true},"cell_type":"code","source":"Responses_2018= pd.read_csv('../input/cdp-unlocking-climate-solutions/Cities/Cities Responses/2018_Full_Cities_Dataset.csv')\nResponses_2019= pd.read_csv('../input/cdp-unlocking-climate-solutions/Cities/Cities Responses/2019_Full_Cities_Dataset.csv')\nResponses_2020= pd.read_csv('../input/cdp-unlocking-climate-solutions/Cities/Cities Responses/2020_Full_Cities_Dataset.csv')\n\n\nData2= Responses_2018.append([Responses_2018,Responses_2019, Responses_2020])\nx = Data2.iloc[:, [3]].values\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Data2['CDP_Region'] = Data2['CDP Region']\nData2['Account_Number'] = Data2['Account Number']\nData2['Parent_Section'] = Data2['Parent Section']\nData2['Question_Number'] = Data2['Question Number']\nData2['Question_Name'] = Data2['Question Name']\nData2['Response_Answer'] = Data2['Response Answer']\nData2['Last_update'] = Data2['Last update']\nData2","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Account_Number"},{"metadata":{"trusted":true},"cell_type":"code","source":"import plotly.express as px\nfrom plotly.subplots import make_subplots\nimport plotly.graph_objs as go\n\ncr = Data2['Account_Number'].value_counts().reset_index()\ncr.columns = [\n    'Account_Number', \n    'count'\n]\ncr['Account_Number'] = cr['Account_Number'].astype(str) + '-'\ncr = cr.sort_values(['count']).tail(50)\n\nfig = px.bar(\n    cr, \n    x='count', \n    y='Account_Number', \n    orientation='h', \n    title='Top 50 users (Account_Number) by number of actions', \n    width=500,\n    height=900 \n)\n\nfig.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Question_Number"},{"metadata":{"trusted":true},"cell_type":"code","source":"cr = Data2['Question_Number'].value_counts().reset_index()\ncr.columns = [\n    'Question_Number', \n    'percent'\n]\ncr['percent'] /= len(Data2)\n\nfig = px.pie(\n    cr, \n    names='Question_Number', \n    values='percent', \n    title='User questions', \n    width=1000,\n    height=500 \n)\n\nfig.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Number of Section"},{"metadata":{"trusted":true},"cell_type":"code","source":"cnt_pro = Data2['Section'].value_counts()  [:50]\nplt.figure(figsize=(6,4))\nsns.barplot(cnt_pro.index, cnt_pro.values, alpha=0.8)\nplt.ylabel('Number of Section', fontsize=12)\nplt.xlabel('Section', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"In the chart above, you can see in the far left Citywide GHG Emission Data of a number of sections were higher that has the amount at least 250000."},{"metadata":{},"cell_type":"markdown","source":"## Number of Parent Section"},{"metadata":{"trusted":true},"cell_type":"code","source":"cnt_pro = Data2['Parent Section'].value_counts()  [:50]\nplt.figure(figsize=(6,4))\nsns.barplot(cnt_pro.index, cnt_pro.values, alpha=0.8)\nplt.ylabel('Number of Parent Section', fontsize=12)\nplt.xlabel('Parent Section', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"In the chart above, you can see in the far left Emissions Reductions of a number of sections were higher that has the amount at least 24000.\n"},{"metadata":{},"cell_type":"markdown","source":"# Cities_Responses each Country"},{"metadata":{"trusted":true},"cell_type":"code","source":"def Cities_Responses(x):\n    y = Data2[[\"Country\",\"Account_Number\",\"Organization\",\"Section\",\"CDP_Region\",\"Question_Number\",\"Question_Name\", \"Response_Answer\",\"Last_update\"]][Data2[\"Country\"] == x]\n    y = y.sort_values(by=\"Account_Number\",ascending=False)\n    return y.head(500)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Brazil"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Brazil\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Portugal"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Portugal\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Malaysia"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Malaysia\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Denmark"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Denmark\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Argentina"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Argentina\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Mexico"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Mexico\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Costa Rica"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Costa Rica\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Netherlands"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Netherlands\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Turkey"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Turkey\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Ecuador"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Ecuador\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Colombia"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Colombia\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Honduras"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Honduras\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Namibia"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Namibia\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Sweden"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Sweden\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Colombia"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Colombia\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Argentina"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Argentina\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## United Kingdom of Great Britain and Northern Ireland"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"United Kingdom of Great Britain and Northern Ireland\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Philippines"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Philippines\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Peru"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Peru\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Germany"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Germany\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## France"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"France\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Norway"},{"metadata":{"trusted":true},"cell_type":"code","source":"\nCities_Responses(\"Norway\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Canada"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Canada\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Italy"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Italy\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Indonesia"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Indonesia\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## India"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"India\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## United States of America"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"United States of America\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Thailand"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Thailand\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## China"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"China\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Republic of Korea"},{"metadata":{"trusted":true},"cell_type":"code","source":"Cities_Responses(\"Republic of Korea\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Full_Cities_Response= pd.read_csv('../input/cdp-unlocking-climate-solutions/Cities/Cities Responses/Full_Cities_Response_Data_Dictionary.csv')\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Full_Cities_Response.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"field = Full_Cities_Response['field'].value_counts()  [:100]\nplt.figure(figsize=(6,4))\nsns.barplot(field.index, field.values, alpha=0.8)\nplt.ylabel('Number of field', fontsize=12)\nplt.xlabel('field', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Corporations"},{"metadata":{},"cell_type":"markdown","source":"## Climate Change"},{"metadata":{"trusted":true},"cell_type":"code","source":"Climate_Change_2018= pd.read_csv('../input/cdp-unlocking-climate-solutions/Corporations/Corporations Disclosing/Climate Change/2018_Corporates_Disclosing_to_CDP_Climate_Change.csv')\nClimate_Change_2019= pd.read_csv('../input/cdp-unlocking-climate-solutions/Corporations/Corporations Disclosing/Climate Change/2019_Corporates_Disclosing_to_CDP_Climate_Change.csv')\nClimate_Change_2020= pd.read_csv('../input/cdp-unlocking-climate-solutions/Corporations/Corporations Disclosing/Climate Change/2020_Corporates_Disclosing_to_CDP_Climate_Change.csv')\n\n\nData3= Climate_Change_2018.append([Climate_Change_2018,Climate_Change_2019, Climate_Change_2020])\nx = Data2.iloc[:, [3]].values\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Data3.head()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Governance"},{"metadata":{},"cell_type":"markdown","source":"## Organization\t"},{"metadata":{"trusted":true},"cell_type":"code","source":"org = Data3.sort_values(by='account_number', ascending=True)[:50]\nfigure = plt.figure(figsize=(10,6))\nsns.barplot(y=org.organization, x=org.account_number)\nplt.xticks(rotation=90)\nplt.xlabel('account_number')\nplt.ylabel('organization ')\nplt.title('Number of organization')\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Minimum_tier"},{"metadata":{"trusted":true},"cell_type":"code","source":"min_tier = Data3['minimum_tier'].value_counts()  [:50]\nplt.figure(figsize=(6,4))\nsns.barplot(min_tier.index, min_tier.values, alpha=0.8)\nplt.ylabel('Number of minimum_tier', fontsize=12)\nplt.xlabel('minimum_tier', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Authority_types"},{"metadata":{"trusted":true},"cell_type":"code","source":"A_type = Data3['authority_types'].value_counts()  [:50]\nplt.figure(figsize=(6,4))\nsns.barplot(A_type.index, A_type.values, alpha=0.8)\nplt.ylabel('Number of Authority_types', fontsize=12)\nplt.xlabel('authority_types', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Activities"},{"metadata":{"trusted":true},"cell_type":"code","source":"Act = Data3['activities'].value_counts()  [:50]\nplt.figure(figsize=(6,4))\nsns.barplot(Act.index, Act.values, alpha=0.8)\nplt.ylabel('Number of activities', fontsize=12)\nplt.xlabel('activities', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Sectors\t"},{"metadata":{"trusted":true},"cell_type":"code","source":"sectors = Data3['sectors'].value_counts()  [:50]\nplt.figure(figsize=(6,4))\nsns.barplot(sectors.index, sectors.values, alpha=0.8)\nplt.ylabel('Number of sectors', fontsize=12)\nplt.xlabel('sectors', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Industries\t"},{"metadata":{"trusted":true},"cell_type":"code","source":"industry = Data3['industries'].value_counts()  [:50]\nplt.figure(figsize=(6,4))\nsns.barplot(industry.index, industry.values, alpha=0.8)\nplt.ylabel('Number of industries', fontsize=12)\nplt.xlabel('industries', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Primary_industry"},{"metadata":{"trusted":true},"cell_type":"code","source":"P_industry = Data3['primary_industry'].value_counts()  [:50]\nplt.figure(figsize=(6,4))\nsns.barplot(P_industry.index, P_industry.values, alpha=0.8)\nplt.ylabel('Number of primary_industry', fontsize=12)\nplt.xlabel('primary_industry', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Primary_sector\t"},{"metadata":{"trusted":true},"cell_type":"code","source":"P_sector = Data3['primary_sector'].value_counts()  [:50]\nplt.figure(figsize=(6,4))\nsns.barplot(P_sector.index, P_sector.values, alpha=0.8)\nplt.ylabel('Number of primary_sector', fontsize=12)\nplt.xlabel('primary_sector', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"display(Data3[Data3[\"public\"]==\"public\"][[\"country\",\"response_received_date\",\"authority_types\",\"activities\",\"sectors\",\"industries\",\"primary_questionnaire_sector\",\n                                       \"survey_year\"]].sort_values(by=\"survey_year\", ascending= False).head(500).style.background_gradient(cmap=\"spring\"))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Climate_Change_Dict= pd.read_csv('../input/cdp-unlocking-climate-solutions/Corporations/Corporations Disclosing/Climate Change/Corporations_Disclosing_to_CDP_Data_Dictionary.csv')\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Climate_Change_Dict.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Climate_Change_Dict = Climate_Change_Dict['field'].value_counts()  [:50]\nplt.figure(figsize=(6,4))\nsns.barplot(Climate_Change_Dict.index, Climate_Change_Dict.values, alpha=0.8)\nplt.ylabel('Number of field', fontsize=12)\nplt.xlabel('field', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Water Security\n\nUN-Water proposes the following definition of water security: \"The capacity of a population to safeguard sustainable access to adequate quantities of acceptable quality water for sustaining livelihoods, human well-being, and socio-economic development, for ensuring protection against water-borne pollution and water-related disasters, and for preserving ecosystems in a climate of peace and political stability\n\nsource :https://www.unwater.org/publications/water-security-infographic/\n"},{"metadata":{"trusted":true},"cell_type":"code","source":"Water_Security_2018= pd.read_csv('../input/cdp-unlocking-climate-solutions/Corporations/Corporations Disclosing/Water Security/2018_Corporates_Disclosing_to_CDP_Water_Security.csv')\nWater_Security_2019= pd.read_csv('../input/cdp-unlocking-climate-solutions/Corporations/Corporations Disclosing/Water Security/2019_Corporates_Disclosing_to_CDP_Water_Security.csv')\nWater_Security_2020= pd.read_csv('../input/cdp-unlocking-climate-solutions/Corporations/Corporations Disclosing/Water Security/2020_Corporates_Disclosing_to_CDP_Water_Security.csv')\n\n\nData4= Water_Security_2018.append([Water_Security_2018,Water_Security_2019, Water_Security_2020])\nx = Data4.iloc[:, [3]].values\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Data4.head()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Governance"},{"metadata":{},"cell_type":"markdown","source":"## organization"},{"metadata":{"trusted":true},"cell_type":"code","source":"org = Data4.sort_values(by='account_number', ascending=True)[:50]\nfigure = plt.figure(figsize=(10,6))\nsns.barplot(y=org.organization, x=org.account_number)\nplt.xticks(rotation=90)\nplt.xlabel('account_number')\nplt.ylabel('organization ')\nplt.title('Number of organization')\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Country"},{"metadata":{"trusted":true},"cell_type":"code","source":"country = Data4['country'].value_counts() \nplt.figure(figsize=(6,4))\nsns.barplot(country.index, country.values, alpha=0.8)\nplt.ylabel('Number of country', fontsize=12)\nplt.xlabel('country', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## samples\t"},{"metadata":{"trusted":true},"cell_type":"code","source":"smp = Data4['samples'].value_counts()  \nplt.figure(figsize=(6,4))\nsns.barplot(smp.index, smp.values, alpha=0.8)\nplt.ylabel('Number of samples', fontsize=12)\nplt.xlabel('samples', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Minimum_tier"},{"metadata":{"trusted":true},"cell_type":"code","source":"min_tier = Data4['minimum_tier'].value_counts()  \nplt.figure(figsize=(6,4))\nsns.barplot(min_tier.index, min_tier.values, alpha=0.8)\nplt.ylabel('Number of minimum_tier', fontsize=12)\nplt.xlabel('minimum_tier', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Authority_types"},{"metadata":{"trusted":true},"cell_type":"code","source":"A_type = Data4['authority_types'].value_counts()  [:50]\nplt.figure(figsize=(6,4))\nsns.barplot(A_type.index, A_type.values, alpha=0.8)\nplt.ylabel('Number of Authority_types', fontsize=12)\nplt.xlabel('authority_types', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":" ## Activities"},{"metadata":{"trusted":true},"cell_type":"code","source":"Act = Data4['activities'].value_counts()  [:50]\nplt.figure(figsize=(6,4))\nsns.barplot(Act.index, Act.values, alpha=0.8)\nplt.ylabel('Number of activities', fontsize=12)\nplt.xlabel('activities', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Sectors"},{"metadata":{"trusted":true},"cell_type":"code","source":"sectors = Data4['sectors'].value_counts()  [:50]\nplt.figure(figsize=(6,4))\nsns.barplot(sectors.index, sectors.values, alpha=0.8)\nplt.ylabel('Number of sectors', fontsize=12)\nplt.xlabel('sectors', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Industries"},{"metadata":{"trusted":true},"cell_type":"code","source":"industry = Data4['industries'].value_counts()  [:50]\nplt.figure(figsize=(6,4))\nsns.barplot(industry.index, industry.values, alpha=0.8)\nplt.ylabel('Number of industries', fontsize=12)\nplt.xlabel('industries', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Primary_industry"},{"metadata":{"trusted":true},"cell_type":"code","source":"P_industry = Data4['primary_industry'].value_counts()  [:50]\nplt.figure(figsize=(6,4))\nsns.barplot(P_industry.index, P_industry.values, alpha=0.8)\nplt.ylabel('Number of primary_industry', fontsize=12)\nplt.xlabel('primary_industry', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Primary_sector"},{"metadata":{"trusted":true},"cell_type":"code","source":"P_sector = Data4['primary_sector'].value_counts()  [:50]\nplt.figure(figsize=(6,4))\nsns.barplot(P_sector.index, P_sector.values, alpha=0.8)\nplt.ylabel('Number of primary_sector', fontsize=12)\nplt.xlabel('primary_sector', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"display(Data4[Data4[\"public\"]==\"public\"][[\"country\",\"authority_types\",\"samples\",\"minimum_tier\",\"activities\",\"sectors\",\"industries\",\"primary_questionnaire_sector\",\n                                       \"survey_year\"]].sort_values(by=\"survey_year\", ascending= False).head(100).style.background_gradient(cmap=\"spring\"))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"def Water_Security(x):\n    y = Data4[[\"account_number\",\"country\",\"organization\",\"region\",\"samples\",\"minimum_tier\",\"response_received_date\",\"sectors\", \"industries\",\"primary_ticker\"]][Data4[\"country\"] == x]\n    y = y.sort_values(by=\"account_number\",ascending=False)\n    return y.head(100)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# United States of America"},{"metadata":{"trusted":true},"cell_type":"code","source":"Water_Security(\"United States of America\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Canada"},{"metadata":{"trusted":true},"cell_type":"code","source":"Water_Security(\"Canada\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Water_Security_Dict= pd.read_csv('../input/cdp-unlocking-climate-solutions/Corporations/Corporations Disclosing/Water Security/Corporations_Disclosing_to_CDP_Data_Dictionary.csv')\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Water_Security_Dict.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Water_Security_Dict = Water_Security_Dict['field'].value_counts()  [:50]\nplt.figure(figsize=(6,4))\nsns.barplot(Water_Security_Dict.index,Water_Security_Dict.values, alpha=0.8)\nplt.ylabel('Number of field', fontsize=12)\nplt.xlabel('field', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Corporations Responses"},{"metadata":{},"cell_type":"markdown","source":"# Climate Change"},{"metadata":{"trusted":true},"cell_type":"code","source":"Full_Climate_Change_2018= pd.read_csv('../input/cdp-unlocking-climate-solutions/Corporations/Corporations Responses/Climate Change/2018_Full_Climate_Change_Dataset.csv')\nFull_Climate_Change_2019= pd.read_csv('../input/cdp-unlocking-climate-solutions/Corporations/Corporations Responses/Climate Change/2019_Full_Climate_Change_Dataset.csv')\nFull_Climate_Change_2020= pd.read_csv('../input/cdp-unlocking-climate-solutions/Corporations/Corporations Responses/Climate Change/2020_Full_Climate_Change_Dataset.csv')\n\n\nData5= Full_Climate_Change_2018.append([Full_Climate_Change_2018,Full_Climate_Change_2019, Full_Climate_Change_2020])\nx = Data5.iloc[:, [3]].values\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Data5.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"org = Data5.sort_values(by='account_number', ascending=True)\nfigure = plt.figure(figsize=(15,6))\nsns.barplot(y=org.organization, x=org.account_number)\nplt.xticks(rotation=50)\nplt.xlabel('account_number')\nplt.ylabel('organization ')\nplt.title('Number of organization')\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"display(Data5[Data5[\"survey_year\"]==\"2020\"][[\"organization\",\"ors_response_id\",\"question_unique_reference\",\"data_point_name\",\"data_point_id\",\"response_value\",\n                                       \"account_number\"]].sort_values(by=\"account_number\", ascending= False).head(5).style.background_gradient(cmap=\"spring\"))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Full_Corporations_Response_Data_Dict= pd.read_csv('../input/cdp-unlocking-climate-solutions/Corporations/Corporations Responses/Climate Change/Full_Corporations_Response_Data_Dictionary copy.csv')\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Full_Corporations_Response_Data_Dict.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Full_Corporations_Response_Data_Dict = Full_Corporations_Response_Data_Dict['field'].value_counts() [:50]\nplt.figure(figsize=(6,4))\nsns.barplot(Full_Corporations_Response_Data_Dict.index,Full_Corporations_Response_Data_Dict.values, alpha=0.8)\nplt.ylabel('Number of field', fontsize=12)\nplt.xlabel('field', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Water Security"},{"metadata":{"trusted":true},"cell_type":"code","source":"Full_Water_Security_2018= pd.read_csv('../input/cdp-unlocking-climate-solutions/Corporations/Corporations Responses/Water Security/2018_Full_Water_Security_Dataset.csv')\nFull_Water_Security_2019= pd.read_csv('../input/cdp-unlocking-climate-solutions/Corporations/Corporations Responses/Water Security/2019_Full_Water_Security_Dataset.csv')\nFull_Water_Security_2020= pd.read_csv('../input/cdp-unlocking-climate-solutions/Corporations/Corporations Responses/Water Security/2020_Full_Water_Security_Dataset.csv')\n\n\nData6= Full_Water_Security_2018.append([Full_Water_Security_2018,Full_Water_Security_2019, Full_Water_Security_2020])\nx = Data6.iloc[:, [3]].values\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Data6.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"cr = Data6['question_number'].value_counts().reset_index()\ncr.columns = [\n    'question_number', \n    'percent'\n]\ncr['percent'] /= len(Data6)\n\nfig = px.pie(\n    cr, \n    names='question_number', \n    values='percent', \n    title='User questions (Water Security)', \n    width=800,\n    height=500 \n)\n\nfig.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"display(Data6[Data6[\"survey_year\"]==\"2019\"][[\"organization\",\"response_received_date\",\"accounting_period_to\",\"ors_response_id\",\"question_unique_reference\",\"data_point_name\",\"data_point_id\",\"row_number\",\"response_value\",\n                                       \"survey_year\"]].sort_values(by=\"survey_year\", ascending= False).head(5).style.background_gradient(cmap=\"spring\"))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Full_Corporations_Response_Data_Dict= pd.read_csv('../input/cdp-unlocking-climate-solutions/Corporations/Corporations Responses/Water Security/Full_Corporations_Response_Data_Dictionary.csv')\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Full_Corporations_Response_Data_Dict","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Full_Corporations_Response_Data_Dict = Full_Corporations_Response_Data_Dict['field'].value_counts()\nplt.figure(figsize=(6,4))\nsns.barplot(Full_Corporations_Response_Data_Dict.index,Full_Corporations_Response_Data_Dict.values, alpha=0.8)\nplt.ylabel('Number of field', fontsize=12)\nplt.xlabel('field', fontsize=9)\nplt.xticks(rotation=90)\nplt.show();","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Supplementary Data"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities_Census_Tract_Data= pd.read_csv('../input/cdp-unlocking-climate-solutions/Supplementary Data/CDC 500 Cities Census Tract Data/500_Cities__Census_Tract-level_Data__GIS_Friendly_Format___2019_release.csv')\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch."},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities_Census_Tract_Data","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Health Census Information"},{"metadata":{},"cell_type":"markdown","source":"## ACCESS2_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"ACCESS2_CrudePrev\",\"ACCESS2_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"ACCESS2_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## ARTHRITIS_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"ARTHRITIS_CrudePrev\",\"ARTHRITIS_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"ARTHRITIS_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"ARTHRITIS_CrudePrev\",\"ARTHRITIS_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## BINGE_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"BINGE_CrudePrev\",\"BINGE_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"BINGE_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"BINGE_CrudePrev\",\"BINGE_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## BPHIGH_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"BPHIGH_CrudePrev\",\"BPHIGH_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"BPHIGH_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"BPHIGH_CrudePrev\",\"BPHIGH_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## BPMED_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"BPMED_CrudePrev\",\"BPMED_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"BPMED_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"BPMED_CrudePrev\",\"BPMED_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## CANCER_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"CANCER_CrudePrev\",\"CANCER_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"CANCER_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"CANCER_CrudePrev\",\"CANCER_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## CASTHMA_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"CASTHMA_CrudePrev\",\"CASTHMA_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"CASTHMA_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"CASTHMA_CrudePrev\",\"CASTHMA_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## CHD_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"CHD_CrudePrev\",\"CHD_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"CHD_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"CHD_CrudePrev\",\"CHD_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"CHECKUP_CrudePrev\",\"CHECKUP_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"CHECKUP_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"CHECKUP_CrudePrev\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## CHOLSCREEN_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"CHOLSCREEN_CrudePrev\",\"CHOLSCREEN_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"CHOLSCREEN_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"CHOLSCREEN_CrudePrev\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## COLON_SCREEN_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"COLON_SCREEN_CrudePrev\",\"COLON_SCREEN_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"COLON_SCREEN_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"COLON_SCREEN_CrudePrev\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## COPD_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"COPD_CrudePrev\",\"COPD_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"COPD_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"COPD_CrudePrev\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## COREM_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"COREM_CrudePrev\",\"COREM_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"COREM_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"COREM_CrudePrev\",\"COREM_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## COREW_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"COREW_CrudePrev\",\"COREW_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"COREW_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"COREW_CrudePrev\",\"COREW_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## CSMOKING_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"CSMOKING_CrudePrev\",\"CSMOKING_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"CSMOKING_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"CSMOKING_CrudePrev\",\"CSMOKING_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## DENTAL_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"DENTAL_CrudePrev\",\"DENTAL_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"DENTAL_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"DENTAL_CrudePrev\",\"DENTAL_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## DENTAL_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"DIABETES_CrudePrev\",\"DIABETES_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"DIABETES_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"DIABETES_CrudePrev\",\"DIABETES_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## HIGHCHOL_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"HIGHCHOL_CrudePrev\",\"HIGHCHOL_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"HIGHCHOL_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"HIGHCHOL_CrudePrev\",\"HIGHCHOL_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## KIDNEY_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"KIDNEY_CrudePrev\",\"KIDNEY_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"KIDNEY_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"KIDNEY_CrudePrev\",\"KIDNEY_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## LPA_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"LPA_CrudePrev\",\"LPA_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"LPA_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"LPA_CrudePrev\",\"LPA_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## MAMMOUSE_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"MAMMOUSE_CrudePrev\",\"MAMMOUSE_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"MAMMOUSE_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"MAMMOUSE_CrudePrev\",\"MAMMOUSE_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## MHLTH_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"MHLTH_CrudePrev\",\"MHLTH_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"MHLTH_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"MHLTH_CrudePrev\",\"MHLTH_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## OBESITY_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"OBESITY_CrudePrev\",\"OBESITY_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"OBESITY_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"OBESITY_CrudePrev\",\"OBESITY_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## PAPTEST_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"PAPTEST_CrudePrev\",\"PAPTEST_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"PAPTEST_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"PAPTEST_CrudePrev\",\"PAPTEST_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## PHLTH_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"PHLTH_CrudePrev\",\"PHLTH_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"PHLTH_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"PHLTH_CrudePrev\",\"PHLTH_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## SLEEP_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"SLEEP_CrudePrev\",\"SLEEP_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"SLEEP_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"SLEEP_CrudePrev\",\"SLEEP_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## STROKE_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"STROKE_CrudePrev\",\"STROKE_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"STROKE_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"STROKE_CrudePrev\",\"STROKE_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## TEETHLOST_CrudePrev"},{"metadata":{"trusted":true},"cell_type":"code","source":"#display(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"TEETHLOST_CrudePrev\",\"TEETHLOST_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\",\"TEETHLOST_Crude95CI\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))\ndisplay(CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"TEETHLOST_CrudePrev\",\"TEETHLOST_Crude95CI\"]].groupby([\"StateAbbr\",\"PlaceName\"]).agg([\"max\",'mean',\"min\"]).style.background_gradient(cmap=\"cool\"))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# CDC 500 Cities Census Tract Data by StateAbbr\t"},{"metadata":{"trusted":true},"cell_type":"code","source":"def CDC_500_Cities(x):\n    y = CDC_500_Cities_Census_Tract_Data[[\"StateAbbr\",\"PlaceName\",\"PlaceFIPS\",\"TractFIPS\",\"Place_TractID\",\"Population2010\",\"ACCESS2_CrudePrev\",\"ACCESS2_Crude95CI\",\"ARTHRITIS_CrudePrev\",\"ARTHRITIS_Crude95CI\",\"BINGE_CrudePrev\",\"BINGE_Crude95CI\",\"BPHIGH_CrudePrev\",\"BPHIGH_Crude95CI\",\"BPMED_CrudePrev\",\"BPMED_Crude95CI\",\"CANCER_CrudePrev\",\"CANCER_Crude95CI\",\"CASTHMA_CrudePrev\",\"CASTHMA_Crude95CI\",\"CHD_CrudePrev\",\"CHD_Crude95CI\",\"CHECKUP_CrudePrev\",\"CHECKUP_Crude95CI\",\"CHOLSCREEN_CrudePrev\",\"CHOLSCREEN_Crude95CI\",\"COLON_SCREEN_CrudePrev\",\"COLON_SCREEN_Crude95CI\",\"COPD_CrudePrev\",\"COPD_Crude95CI\",\"COREM_CrudePrev\",\"COREM_Crude95CI\",\"COREW_CrudePrev\",\"COREW_Crude95CI\",\"CSMOKING_CrudePrev\",\"CSMOKING_Crude95CI\",\"DENTAL_CrudePrev\",\"DENTAL_Crude95CI\",\"DIABETES_CrudePrev\",\n                                          \"DIABETES_Crude95CI\",\"HIGHCHOL_CrudePrev\",\"HIGHCHOL_Crude95CI\",\"KIDNEY_CrudePrev\",\"KIDNEY_Crude95CI\",\"LPA_CrudePrev\",\"LPA_Crude95CI\",\"MAMMOUSE_CrudePrev\",\"MAMMOUSE_Crude95CI\",\"MHLTH_CrudePrev\",\"MHLTH_Crude95CI\",\"OBESITY_CrudePrev\",\"OBESITY_Crude95CI\",\"PAPTEST_CrudePrev\",\"PAPTEST_Crude95CI\",\"PHLTH_CrudePrev\",\"PHLTH_Crude95CI\",\"SLEEP_CrudePrev\",\"SLEEP_Crude95CI\",\"STROKE_CrudePrev\",\"STROKE_Crude95CI\",\"TEETHLOST_CrudePrev\",\"TEETHLOST_Crude95CI\",\"Geolocation\"]][CDC_500_Cities_Census_Tract_Data[\"StateAbbr\"] == x]\n    y = y.sort_values(by=\"Population2010\",ascending=False)\n    return y.head(500)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## AL"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"AL\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## AK"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"AK\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## AZ"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"AZ\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## AR"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"AR\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## CA"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"CA\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## CO"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"CO\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## CT"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"CT\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## DE"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"DE\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## DC"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"DC\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## FL"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"FL\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## GA"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"GA\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## HI"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"HI\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## ID"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"ID\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## IL"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"IL\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## IN"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"IN\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## IA"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"IA\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## KS"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"KS\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## KY"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"KY\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## LA"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"LA\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## ME"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"ME\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## MD"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"MD\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## MA"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"MA\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## MI"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"MI\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## MN"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"MN\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## MS"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"MS\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## MO"},{"metadata":{"trusted":true},"cell_type":"code","source":"CDC_500_Cities(\"MO\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## 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