{"cells":[{"metadata":{},"cell_type":"markdown","source":"<div align='center'><font size=\"5\" color='#088a5a'>Unlocking Insights from CDP Surve Data: Measuring Sustainability\n</font></div>\n<div align='center'><font size=\"4\" color=\"#088a5a\">A detailed comparative analysis on the future of eco-KPIs</font></div>\n<hr>\n\n<p>The measurement of what we call a city’s ‘sustainability’ has also changed greatly over time. We might say that sustainability used to be about measuring the level of pollution and the amount of parkland. In the 1990s, many cities began to take a new approach to balancing their environmental, social and economic impact, using metrics not only to measure factors such as energy, water use and pollution but also to address concerns such as crime, employment and health. With the exploding amount of urban data, the metrics have become more complex, and their uses have expanded, particularly as the government addresses a wider range of environmental and social needs. When we measure cities now, we are seeking to understand them in order to manage them better and to provide evidence of performance. Increasingly, we measure cities to understand their sustainability and to make decisions that will allow those who live in them to be happier and healthier in the future. \n </p>\n\n<img src='https://i2.wp.com/wearerestless.org/wp-content/uploads/2016/11/HiRes.jpg?zoom=2&resize=1155%2C770&ssl=1' width=500>\n<div align=\"center\"><font size=\"2\">Source: wearerestless.org</font></div>  \n\n \nA carefully selected and relatively small number of easily understandable Key Performance Indicators (KPI) is useful for city managers to get a snapshot of the city's performance in different areas. The question of interest in this analysis is: **does setting up plans/targets promote sustainability performance?**\n\n\n\n\n"},{"metadata":{},"cell_type":"markdown","source":"<font color='#088a5a' size=5>Contents</font><br>\n\n<a href=\"#1\">1. Lessons from Working with Survey Data</a>   \n<a href=\"#2\">2. Modified Green City Index (MGCI): Constructing 8 Axes from CDP Survey</a>  \n<a href=\"#3\">3. Analysis on Corporate + City: CDP Answer Mining</a>   \n<a href=\"#4\">4. Does setting up plans/targets promote sustainability performance?</a>   \n<a href=\"#5\">5. Concluding Remarks: Actionable Insights</a>   \n<a href=\"#6\">6. References</a>  "},{"metadata":{},"cell_type":"markdown","source":"<div id=\"#1\"></div>\n<font color='#088a5a' size=5>1. Lessons from Working with Survey Data</font><br>            \n\nIn this section, we start with looking at 2 dimensions of city development strategy by analyzing 2 specific questions from the city survey.\n"},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"# standard libs\nimport os\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport re\nimport json\n\n# plotting libs\nimport seaborn as sns\n\n# geospatial libs\nfrom mpl_toolkits.basemap import Basemap\nfrom shapely.geometry import Polygon\nimport geopandas as gpd\nimport folium\nimport plotly.graph_objects as go\nimport plotly_express as px\n\n# set in line plotly \nfrom plotly.offline import init_notebook_mode;\ninit_notebook_mode(connected=True)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# import corporate response data\ncc_df = pd.read_csv('../input/cdp-unlocking-climate-solutions/Corporations/Corporations Responses/Climate Change/2020_Full_Climate_Change_Dataset.csv',dtype={\"Response Answer\":\"string\",\"comments\": \"string\"})\nws_df = pd.read_csv('../input/cdp-unlocking-climate-solutions/Corporations/Corporations Responses/Water Security/2020_Full_Water_Security_Dataset.csv',dtype={\"comments\": \"string\"})\ncc_df = pd.concat([cc_df, ws_df],ignore_index=True)\ncc_df.rename(columns = {'question_unique_reference':'Question Name','response_value':'Response Answer'}, inplace = True)\n\n# import city responses\ncity_df = pd.read_csv('../input/cdp-unlocking-climate-solutions/Cities/Cities Responses/2020_Full_Cities_Dataset.csv',dtype={\"Response Answer\":\"string\",\"comments\": \"string\"})\ncity_df = city_df.fillna('Do not know')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"qs_city = city_df['Question Name'].unique()\nqs = qs_city","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"def get_q(df = city_df, keyword = \"\"):\n    qs = df['Question Name'].unique()\n    matching = [(i,s) for i,s in enumerate(qs) if keyword in s]\n    return matching\n\ndef get_ans(df, qnum):\n    qs = df['Question Name'].unique()\n    return df[df[\"Question Name\"] == qs[qnum]][\"Response Answer\"]\n\ndef combine_ans(df, phrase):\n    sep = []\n    if type(phrase) == list:\n        # set of answers that contain all phrases\n        for p in phrase:\n            tmp = [i[0] for i in get_q(df,p)]\n            sep.append(tmp)\n        q_num = set.intersection(*map(set,sep))\n            \n    else:\n        q_num = [i[0] for i in get_q(df,phrase)]\n        \n    ans_list = []\n    for q in q_num:\n        ans_list.append(' '.join([i for i in list(get_ans(df, q).unique()) if type(i) == str]))\n\n    all_ans = ' '.join([str(elem) for elem in ans_list]) \n    all_ans = all_ans.replace(\"Other, please specify:\",\" \")\n    return all_ans\n\ndef generate_wraptxt(txt, linewidth=40): \n    tit = wrap(txt, width=linewidth)\n    return '\\n'.join(tit)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"q1='Does your city incorporate sustainability goals and targets (e.g. GHG reductions) into the master planning for the city?'\nq2 = 'Does your city collaborate in partnership with businesses in your city on sustainability projects?'","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"pref_color = [ '#9FF781','#CEF6D8',  '#F7819F', '#F5A9BC','#E6E6E6']\ndds = [city_df.groupby('Question Name').get_group(q1)[\"Response Answer\"].value_counts(),\\\n      city_df.groupby('Question Name').get_group(q2)[\"Response Answer\"].value_counts()]\nq = [q1, q2]\n\nfor i,dd in enumerate(dds):\n    xx = list(dd.keys())\n\n    # matplotlib general settings\n    fig, ax = plt.subplots(figsize=(20,1))\n    plt.title(q[i], fontsize=18, loc='left')\n    ax.get_xaxis().set_visible(False)\n    ax.tick_params(axis='y', labelsize=16, labelcolor='grey')  \n    ax.set_facecolor('white')\n    ax.axis('off')\n    # Draw each bar and text separately with appropriate offset\n    bar_start = 0\n    cnts = [dd[_]/np.sum(list(dd.values)) for _ in xx]\n\n    for i in range(len(dd)):\n        ax.barh(y=['All Respondents'], width=cnts[i], height=0.1, left=bar_start, color=pref_color[i])\n        plt.text(bar_start + cnts[i]/2 - 0.01, -0.01, \"{:.0%}\".format(cnts[i]), fontsize=16)\n        bar_start += cnts[i]\n\n#     Draw legend and set color of its text\n    leg = ax.legend(xx, loc=(0,-0.5), ncol=5, fontsize=14, frameon=True, facecolor='white');\n    for txt in leg.get_texts():\n        plt.setp(txt, color='grey')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from textwrap import wrap\nbarcolors = [\"#fad46b\",\"#97c6e8\"]\nbarstyle = {\"edgecolor\":\"black\", \"linewidth\":0.5}\n\n# build a city questions df\nd =  {'city': city_df['Organization'].unique()}\ndf_cityQ = pd.DataFrame(data = d)\nmapping_country = dict(city_df[['Organization', 'Country']].values)\ndf_cityQ['Country'] = df_cityQ['city'].map(mapping_country)\n\nq = {'q1': q1, 'q2':q2}\nfor k,val in q.items():\n    options = city_df.groupby('Question Name').get_group(val)[\"Response Answer\"].value_counts().keys()\n    options_map = {}\n    for i in np.arange(len(options)):\n        options_map[options[i]] = i\n\n    df_cityQ[k] = pd.DataFrame(city_df.groupby('Question Name').get_group(val)[\"Response Answer\"]).reset_index(drop = True)\n#     df_cityQ[k] = df_cityQ[k].map(options_map) # convert to numeric values","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import matplotlib.pyplot as plt\nfrom matplotlib_venn import venn2, venn3, venn3_circles\n\nplt.figure(figsize=(6,6))\nvd3=venn3([set(df_cityQ[df_cityQ['q1'] == 'Yes']['city']), set(df_cityQ[df_cityQ['q2'] == 'Yes']['city']),\\\n      set(df_cityQ['city'])],\n set_labels= ('Cities incorporating \\n sustainability goal',\\\n                    'Cities collaborating with businesses \\n on sustainability projects','All cities'),\n set_colors=('#c4e6ff', '#F4ACB7','#9D8189'), \n alpha = 0.8)\n\nc=venn3_circles([set(df_cityQ[df_cityQ['q1'] == 'Yes']['city']), set(df_cityQ[df_cityQ['q2'] == 'Yes']['city']),\\\n      set(df_cityQ['city'])], linestyle='-.', linewidth=2, color='grey')\nfor text in vd3.set_labels:\n    text.set_fontsize(16);\n# for text in vd3.subset_labels:\n#     text.set_fontsize(16)\nplt.title('Comparison of city responses: Sustainability development',fontname='Times New Roman',fontweight='bold',fontsize=20,\n pad=30,backgroundcolor='#cbe7e3',color='black',style='italic');\n\nplt.annotate('Planning-first', xy=(-0.3,-0.3), xytext=(0.05,0.1),\nha='center', textcoords= 'axes fraction', bbox=dict(boxstyle='round,pad=0.5', fc='gray', alpha=0.1),\narrowprops=dict(arrowstyle='<-', connectionstyle='arc3,rad=0.5',color='gray'))\n\nplt.annotate('Collaborating-first', xy=(0.4,0.2), xytext=(1.2,0.3),\nha='center', textcoords= 'axes fraction', bbox=dict(boxstyle='round,pad=0.5', fc='gray', alpha=0.1),\narrowprops=dict(arrowstyle='<-', connectionstyle='arc3,rad=0.5',color='gray'))\n\nplt.annotate('Planning and Collaborating interrelated', xy=(0.1,-0.2), xytext=(1.1,0.1),\nha='center', textcoords= 'axes fraction', bbox=dict(boxstyle='round,pad=0.5', fc='gray', alpha=0.1),\narrowprops=dict(arrowstyle='<-', connectionstyle='arc3,rad=0.5',color='gray'))\n\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"While proactive environmental initiatives may create an unique edge, such strategy requires substantial resources, management capabilities and long-term commitment. To achieve this, some cities may choose to cooperate with firms, by pooling resources to create synergies and innovative strategies to boost sustainability. The Venn Diagram above shows the number of cities that take different development strategies."},{"metadata":{"trusted":true},"cell_type":"code","source":"from matplotlib import cm\nheatmap_args = dict(annot=True, fmt=\"d\", square=False, cmap=cm.get_cmap(\"Greens\",12), \n               center = 90, vmin=0, vmax=500, lw=4, \n               cbar=False)\ndef hide_axes(this_ax):\n    this_ax.set_frame_on(False)\n    this_ax.set_xticks([])\n    this_ax.set_yticks([])\n    return this_ax\n\ndef draw_border_around_axes(this_ax, color=\"black\"):\n    for axis in ['top','bottom','left','right']:\n        this_ax.spines[axis].set_visible(True)\n        this_ax.spines[axis].set_color(color)\n        \ndef draw_code_ml_heatmap_general(df,tmp_ax,**kwargs):\n    hm = sns.heatmap(df, ax = tmp_ax, \n                **kwargs)\n    tmp_ax.set_xlabel('Q1')\n    tmp_ax.set_ylabel('Q2')\n    tmp_ax.set_yticklabels(tmp_ax.get_yticklabels(), rotation=0);\n    return hm \n    \ndef draw_code_ml_heatmap(tmp_ax):\n    hm = draw_code_ml_heatmap_general(allage_codepivot2, tmp_ax, **heatmap_args)\n    return hm\n\ndef calc_df_hist(df):\n    return df/df.sum().sum()\n\ndef draw_mini_heatmap(df, this_ax, titletxt, linewidth=25, **kwargs):\n    hm = draw_code_ml_heatmap_general(df, this_ax, **kwargs)\n    this_ax.set_title(generate_wraptxt(titletxt, linewidth));\n    this_ax.set_frame_on(True)\n    this_ax.set_xticks([])\n    this_ax.set_yticks([])\n    this_ax.set_xlabel('')\n    this_ax.set_ylabel('')\n    draw_border_around_axes(this_ax)\n    return hm ","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"heatmap_args_nolim = dict(annot=True, fmt=\"d\", square=False, cmap=cm.get_cmap(\"Greens\",12), \n               lw=4, cbar=False)\nheatmap_args_ref = heatmap_args_nolim.copy()\nheatmap_args_ref['square']=True\nheatmap_args_ref['annot']=True\nheatmap_args_ref['fmt']='.0f'\nheatmap_args_ref['cmap']=cm.get_cmap('Greens')\nheatmap_args_ref['center']=13\nheatmap_args_ref['vmax']=25\nheatmap_args_ref['vmin']=0\nheatmap_args_ref['annot_kws']={\"size\":7}\n\nheatmap_args_nolim_sq = heatmap_args_nolim.copy()\nheatmap_args_nolim_sq['square']=True\nheatmap_args_nolim_sq['annot']=False\nheatmap_args_nolim_sq['fmt']='.1%'\nheatmap_args_nolim_sq['cmap']=cm.get_cmap('seismic_r',11)\nheatmap_args_nolim_sq['center']=0\nheatmap_args_nolim_sq['vmax']=0.055\nheatmap_args_nolim_sq['vmin']=-0.055\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_cityQ = df_cityQ.replace(\"\", \"Do not know\")\nallage_codepivot2 = pd.crosstab(df_cityQ['q1'], df_cityQ['q2'])\nprefer_order = [0,3,2,1,4]\nallage_codepivot2 = allage_codepivot2[allage_codepivot2.columns[prefer_order]]\n# allage_codepivot2 = allage_codepivot2.reindex(['Do not know','Not intending to incorporate','Intending to incorporate in the next 2 years','In progress','Yes'])\nallage_codepivot2 = allage_codepivot2.reindex(allage_codepivot2.index[prefer_order])\n\nf, ax = plt.subplots(nrows=2, ncols=2, figsize=(9,9), \n                     gridspec_kw={'height_ratios':[2,5], 'width_ratios':[2,5], 'wspace':0.1, 'hspace':0.1})\n\nthis_ax = ax[0,0]\nhide_axes(this_ax)\n\nhm_ax = ax[1,1]\ndraw_code_ml_heatmap(hm_ax);\nhm_ax.yaxis.tick_right()\nhm_ax.yaxis.set_label_position(\"right\")\ndraw_border_around_axes(hm_ax)\n\nthis_ax = ax[0,1]\nallage_codepivot2.sum(axis=0).plot.bar(ax=this_ax, color=barcolors[1],**barstyle)\nthis_ax.set_xlabel(hm_ax.get_xlabel())\nthis_ax.xaxis.set_ticklabels([])\n# this_ax.xaxis.tick_top()\nthis_ax.xaxis.set_label_position(\"top\")\nthis_ax.set_ylabel('# answers')\n\nthis_ax = ax[1,0]\nallage_codepivot2.sum(axis=1)[::-1].plot.barh(ax=this_ax, color=barcolors[0],**barstyle)\nthis_ax.set_ylabel(hm_ax.get_ylabel())\nthis_ax.yaxis.set_label_position(\"left\")\n# this_ax.xaxis.tick_top()\n# this_ax.xaxis.set_label_position(\"top\")\n# this_ax.set_xlim(this_ax.get_xlim()[::-1]);\nthis_ax.set_xlabel('# answers');\nprint(\"Q1: \"+ q1)\nprint(\"Q2: \" + q2)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Interpreting the heatmap:\nOverall, this heatmap above illustrates the distribution of specific clusters of survey takers when it comes to their development priorities. The degree gets higher rightwards and downwards.\n\nMore specificlly,\n - the upper left to lower right diagonal suggests both incorporating sustainability goals and targets into city master planning and collaborating in partnership with businesses at equal weight\n - below the diagonal suggests more focus on collaborations\n - above the diagonal are cities that focus more on planning"},{"metadata":{"trusted":true},"cell_type":"code","source":"refhist = calc_df_hist(allage_codepivot2)\nthis_ax = plt.axes()\nrh = refhist\nheatmap_args_ref2 = heatmap_args_ref.copy()\nheatmap_args_ref2['annot_kws'] = {\"size\":10}\ndraw_mini_heatmap(\n        round((rh)*100), \n        this_ax, \"Across all surveyed cities (%)\", **heatmap_args_ref2);","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Here, we simply normalize the heatmap to percentages."},{"metadata":{"trusted":true},"cell_type":"code","source":"# horizontal comparison\nf, ax = plt.subplots(ncols=3, nrows=1, figsize = (12,4),\n                     gridspec_kw = {\"wspace\":0.75})\n\nthis_ax = ax[0]\ndraw_mini_heatmap(\n        round((refhist)*100), \n        this_ax, \"across all cities (%)\", **heatmap_args_ref2)\n\nfor i, country_name in enumerate(['United States of America', \"Mexico\"]):\n    dat = pd.crosstab(df_cityQ.query('Country == @country_name')['q1'], \\\n                     df_cityQ.query('Country == @country_name')['q2'])\n    dat = dat.reindex(index=df_cityQ['q1'].unique()[[4,3,2,1,0]], \\\n                      columns=df_cityQ['q2'].unique()[[4,3,2,1,0]], fill_value=0)\n    st = calc_df_hist(dat)\n    this_ax = ax[i+1]\n    draw_mini_heatmap(\n            round((st)*100), \n            this_ax, country_name, **heatmap_args_ref2)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"We could compare horizontally the heatmaps for cities from different countries relative to the average across all cities surveyed."},{"metadata":{"trusted":true},"cell_type":"code","source":"import matplotlib.patheffects as path_effects\ndef black_border_around_text(annotation_handle):\n    annotation_handle.set_path_effects([path_effects.Stroke(linewidth=2, foreground='black'),\n                       path_effects.Normal()])\n    return annotation_handle\n\ndef draw_zero_heatmap_legend(this_ax, cbar_ax, df):\n    cbar_kws = dict(orientation=\"horizontal\", ticks=np.arange(-0.06,0.06,0.01))    \n    cbar_pos = cbar_ax.get_position()\n    cbar_ax.set_position([cbar_pos.x0, cbar_pos.y0+cbar_pos.height/2, cbar_pos.width, cbar_pos.height/6])\n\n    zero_kws = heatmap_args_nolim_sq.copy()\n    zero_kws['cbar_ax'] = cbar_ax\n    zero_kws['cbar_kws'] = cbar_kws\n    zero_kws['cbar'] = True\n    \n    hm = draw_mini_heatmap(\n            df, \n            this_ax, \"\", **zero_kws)\n    arrow_y = this_ax.annotate('', xy=(-0.3,5),  xycoords='data',\n                xytext=(-0.3,0.5), \n                arrowprops=dict(arrowstyle=\"->\",color='black'),\n                horizontalalignment='right', verticalalignment='top',annotation_clip=False\n                )\n    this_ax.set_ylabel('more collaborations',labelpad=15)\n\n    arrow_x = this_ax.annotate('', xy=(5,-0.3),  xycoords='data',\n                xytext=(0.5,-0.3), \n                arrowprops=dict(arrowstyle=\"->\",color='black'),\n                horizontalalignment='right', verticalalignment='top',annotation_clip=False\n                )\n    this_ax.set_xlabel('more planning',labelpad=15)\n    this_ax.xaxis.set_label_position('top')\n    \n#     cbar_ax.set_xticks(np.arange(-0.6,0.6,0.1))\n    labels = cbar_ax.get_xticks()*100\n    cbar_ax.set_xticklabels([\"{0:.0f}%\".format(x) for x in labels])\n    cbar_ax.set_title('histogram difference (perc.points)')\n    return hm ","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"f, ax = plt.subplots(ncols=6, nrows=1, figsize = (18,4),\n                     gridspec_kw = {\"width_ratios\":[1,0.1,1,0.25,1,2],\"wspace\":0.25})\n\ncountry_name = \"United States of America\"\n\nthis_ax = ax[0]\ndat = pd.crosstab(df_cityQ.query('Country == @country_name')['q1'], \\\n                     df_cityQ.query('Country == @country_name')['q2'])\n# dat = dat.reindex(index=df_cityQ['q1'].unique(), \\\n#                   columns=df_cityQ['q2'].unique(), fill_value=0)\ndat = dat.reindex(index=df_cityQ['q1'].unique()[[4,3,2,1,0]], \\\n                      columns=df_cityQ['q2'].unique()[[4,3,2,1,0]], fill_value=0)\nst = calc_df_hist(dat)\ndraw_mini_heatmap(\n        round((st)*100), \n        this_ax, country_name, **heatmap_args_ref2)\n\nthis_ax = ax[1]\nan1 = this_ax.annotate(\"-\", xy=(0.5,0.5), fontsize=40, color=\"black\", weight='bold',\n                       verticalalignment='center', horizontalalignment='center', annotation_clip=False)\nblack_border_around_text(an1);\nhide_axes(this_ax)\n\nthis_ax = ax[2]\ndraw_mini_heatmap(\n        round((rh)*100), \n        this_ax, \"all cities surveyed (%)\", **heatmap_args_ref2)\n\nthis_ax = ax[3]\nan1 = this_ax.annotate(\"=\", xy=(0.25,0.5), fontsize=40, color=\"black\", weight='bold',\n               verticalalignment='center', horizontalalignment='center', annotation_clip=False)\nblack_border_around_text(an1);\nhide_axes(this_ax)\n\ndraw_zero_heatmap_legend(ax[4], ax[5], (st-rh));","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Here, we make a instinctive difference between a country (e.g. the US) and global average, and immediately see that the US have on average much <span style=\"background:#3333ff; font-weight:bold; color:white\">more cities with both high priorities in planning and collaborating than average</span>, and there are <span style=\"background:#ff3333; font-weight:bold; color:white\">relatively few cities prioritizing heavily on collaborations</span> in the country. White cells imply no big difference between the selected group and average case."},{"metadata":{"trusted":true},"cell_type":"code","source":"f, ax = plt.subplots(ncols=6, nrows=1, figsize = (18,4),\n                     gridspec_kw = {\"width_ratios\":[1,0.1,1,0.25,1,2],\"wspace\":0.25})\n\ncountry_name = \"United Kingdom of Great Britain and Northern Ireland\"\n\nthis_ax = ax[0]\ndat = pd.crosstab(df_cityQ.query('Country == @country_name')['q1'], \\\n                     df_cityQ.query('Country == @country_name')['q2'])\ndat = dat.reindex(index=df_cityQ['q1'].unique()[[4,3,2,1,0]], \\\n                      columns=df_cityQ['q2'].unique()[[4,3,2,1,0]], fill_value=0)\nst = calc_df_hist(dat)\ndraw_mini_heatmap(\n        round((st)*100), \n        this_ax, country_name, **heatmap_args_ref2)\n\nthis_ax = ax[1]\nan1 = this_ax.annotate(\"-\", xy=(0.5,0.5), fontsize=40, color=\"black\", weight='bold',\n                       verticalalignment='center', horizontalalignment='center', annotation_clip=False)\nblack_border_around_text(an1);\nhide_axes(this_ax)\n\nthis_ax = ax[2]\ndraw_mini_heatmap(\n        round((rh)*100), \n        this_ax, \"all cities surveyed (%)\", **heatmap_args_ref2)\n\nthis_ax = ax[3]\nan1 = this_ax.annotate(\"=\", xy=(0.25,0.5), fontsize=40, color=\"black\", weight='bold',\n               verticalalignment='center', horizontalalignment='center', annotation_clip=False)\nblack_border_around_text(an1);\nhide_axes(this_ax)\n\ndraw_zero_heatmap_legend(ax[4], ax[5], (st-rh));","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Similarly, if we take a look at the UK, we will see that on average it has much <span style=\"background:#3333ff; font-weight:bold; color:white\">more cities with higher priorities in collaborating than average</span>, and there are <span style=\"background:#ff3333; font-weight:bold; color:white\">relatively few cities prioritizing equally on  planning and collaborations</span> in the country."},{"metadata":{},"cell_type":"markdown","source":"<div id=\"#2\"></div>\n<font color='#088a5a' size=5>2. Modified Green City Index (MGCI): Constructing 8 Axes from CDP Survey</font><br>            \n\nIn this part, we will discuss some of the ways in which cities are being measured and how these metrics could evolve. More importantly, it provides practical examples of what leading cities are doing, the lessons to be learned and how these can be applied to other cities.\n\nTo expolre the intersection between environmental issues and social issues, we referenced the well-known green city index and created a modified version where the proxies used to capture the multi-level indicators are sourced from the 2020 CDP survey data. \n\n![image.png](attachment:image.png)\n\n","attachments":{"image.png":{"image/png":"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"}}},{"metadata":{"trusted":true},"cell_type":"code","source":"d = {'Organization': city_df['Organization'].unique()}\ndf_green = pd.DataFrame(data=d)\ncity_country_dict = {}\ncity_region_dict = {}\nfor c in d['Organization']:\n    city_country_dict[c] = city_df[city_df['Organization'] == c]['Country'].unique()[0]\n    city_region_dict[c] = city_df[city_df['Organization'] == c]['CDP Region'].unique()[0]\ndf_green['Country'] = df_green['Organization'].map(city_country_dict)\ndf_green['CDP Region'] = df_green['Organization'].map(city_region_dict)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"def get_ans_unique_cnts(df,qnum):\n    return len(get_ans(df, qnum).value_counts())\n\ndef separate_qs(df, axis):\n    idx = [i[0] for i in axis]\n    multichoice = []\n    texts = []\n    for i in idx:\n        c = get_ans_unique_cnts(df, i)\n        if(c < 10):\n            multichoice.append(i)\n        else:\n            texts.append(i)\n    return multichoice, texts\n\ndef get_ans_per_firm(df, qnum):\n    qs = df['Question Name'].unique()\n    return df[df[\"Question Name\"] == qs[qnum]].groupby(['Organization'])[\"Response Answer\"].apply(','.join).reset_index()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### Grading multiple choice problems and text answer problems differently\n\nSome survey questions are multiple-choice format, where responders simply take one or more choices; while other questions are generally short answer quetions which require providing further information including, but not limited to, the nature of the risks/opportunities, what actions have been done/about to be done, among many others. We deal with these two sets of questions differently, as we compute:\n\n- sentiment scores for short answer questions (i.e., narrative disclosures) using NLP processing\n- numeric scores for multiple choice questions with weights for different options"},{"metadata":{"trusted":true},"cell_type":"code","source":"from nltk.sentiment.vader import SentimentIntensityAnalyzer\n\n# Sentiment analysis for short answer questions\ndef sentiment_score(df, axis, qnum_list):\n    sid = SentimentIntensityAnalyzer()\n    df[axis+'_score'] = 0\n    \n    for q_text in qnum_list:\n        ans_df = get_ans_per_firm(city_df, q_text)\n        df = pd.merge(df, ans_df[['Organization','Response Answer']],on='Organization', how='left')\n\n        for i,ans in enumerate(df['Response Answer']):\n            if type(ans) != str:\n                df.loc[i,axis+'_score'] += 0        \n            else:\n                ss = sid.polarity_scores(ans)\n                df.loc[i,axis+'_score'] += ss['compound'] + ss['pos']\n        del df['Response Answer']\n    return df","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"def choice_score(df, axis, qnum_list):\n#     df[axis+'_grade'] = 0\n    options_map = {'Yes':2, 'No':0, 'Question not applicable': 0.5, 'Do not know':-0.5, \\\n              'In progress': 1.5, 'Intending to':1, \"Not intending to\": -1}\n    \n    for q_text in qnum_list:\n        ans_df = get_ans_per_firm(city_df, q_text)\n        ans_df[ans_df['Response Answer'].str.contains(\"Intending to\")] = \"Intending to\"\n        ans_df[ans_df['Response Answer'].str.contains(\"Not intending to\")] = \"Not intending to\"\n        df = pd.merge(df, ans_df[['Organization','Response Answer']],on='Organization', how='left')\n\n        df[axis+'_score'] += ans_df[\"Response Answer\"].map(options_map).fillna(0.1)\n        del df['Response Answer']\n    return df  ","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# air quality axis\nair = list(set(get_q(city_df,\"air \")) | set(get_q(city_df,\"gas\")) | set(get_q(city_df,\"Air\")))\nair_choice, air_texts = separate_qs(city_df, air)\ndf_green = sentiment_score(df_green, \"air\", air_texts)\ndf_green = choice_score(df_green, \"air\", air_choice)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# governance axis\ngov = list(set(get_q(city_df,\"policy\")) | set(get_q(city_df,\"plan\")) | set(get_q(city_df,\"social\")) | set(get_q(city_df,\"eco\")) | set(get_q(city_df,\"employ\")))\ngov_choice, gov_texts = separate_qs(city_df, gov)\ndf_green = sentiment_score(df_green, \"gov\", gov_texts)\ndf_green = choice_score(df_green, \"gov\", gov_choice)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# co2 axis\nco2 = list(set(get_q(city_df,\"CO2\")) | set(get_q(city_df,\"carbon\")) | set(get_q(city_df,\"GHG\")) | set(get_q(city_df,\"emission\")))\nco2_choice, co2_texts = separate_qs(city_df, co2)\ndf_green = sentiment_score(df_green, \"co2\", co2_texts)\ndf_green = choice_score(df_green, \"co2\", co2_choice)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# energy axis\nenergy = list(set(get_q(city_df,\"energy\")))\nenergy_choice, energy_texts = separate_qs(city_df, energy)\ndf_green = sentiment_score(df_green, \"energy\", energy_texts)\ndf_green = choice_score(df_green, \"energy\", energy_choice)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# building axis\nbuilding = list(set(get_q(city_df,\"building\")))\nbuilding_choice, building_texts = separate_qs(city_df, building)\ndf_green = sentiment_score(df_green, \"building\", building_texts)\ndf_green = choice_score(df_green, \"building\", building_choice)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# extract quantitiative emission information\ntCO2e = city_df.groupby('Question Name').get_group(qs_city[32]) # total CO2 emission\ndf = df_green.copy()\nemit_list = []\nfor i in tCO2e['Row Number'].unique():\n    CO2_div = tCO2e.groupby('Row Number').get_group(i).reset_index(drop = True)\n    df = pd.merge(df,CO2_div[['Organization','Response Answer']],on='Organization', how='left')\n    df.rename(columns = {'Response Answer':CO2_div['Row Name'][0] + '_emission'}, inplace = True)\n    emit_list.append(CO2_div['Row Name'][0] + '_emission')\n    \nfor i in range(len(emit_list)):\n#     df.loc[df[emit_list[i]] == 'Question not applicable',emit_list[i]] = np.nan\n    df[emit_list[i]] = pd.to_numeric(df[emit_list[i]], errors='coerce')\n    \n# df.fillna('Do not know', inplace = True)\ndf['totalCO2e'] = df[emit_list].sum(axis=1)\ndf['country_emit'] = df.groupby('Country')['totalCO2e'].transform('sum')\ndf['country_emit'] = df['country_emit'].replace(0, np.nan)\n\n# emission map for all countries\nimport plotly.express as px\n\nmy_color_scale=cm.get_cmap(\"Greens\",12)\nfig = px.choropleth(df, locations=\"Country\", locationmode='country names',color=\"country_emit\", \\\n                    color_continuous_scale='Greys', hover_name=\"Country\", range_color=[0,25],\\\n                    title = '2020 Emissions of CO2 per capita (metric tonnes) from buildings for Countries Surveyed by CDP <br><i>(only showing the ones that have valid submissions)<i>')\n\nfig.update_layout(geo=dict(\n    countrycolor= \"#444444\",\n    showcountries=True))\nfig.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# transport axis\ntransport = list(set(get_q(city_df,\"transport\")) | set(get_q(city_df,\"car\")))\ntransport_choice, transport_texts = separate_qs(city_df, transport)\ndf_green = sentiment_score(df_green, \"transport\", transport_texts)\ndf_green = choice_score(df_green, \"transport\", transport_choice)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# waste axis\nwaste = list(set(get_q(city_df,\"waste\")))\nwaste_choice, waste_texts = separate_qs(city_df, waste)\ndf_green = sentiment_score(df_green, \"waste\", waste_texts)\ndf_green = choice_score(df_green, \"waste\", waste_choice)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# water axis\nwater = list(set(get_q(city_df,\"water\")))\nwater_choice, water_texts = separate_qs(city_df, water)\ndf_green = sentiment_score(df_green, \"water\", water_texts)\ndf_green = choice_score(df_green, \"water\", water_choice)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# normalize scores along axis\nfrom sklearn.preprocessing import MinMaxScaler, StandardScaler\nfor col in df_green.columns[3:]:\n    scaler=MinMaxScaler()\n    df_green[col] = scaler.fit_transform(df_green[[col]])","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# sum up all score\ncol_list = df_green.columns[3:]\ndf_green['sum'] = df_green[col_list].sum(axis=1)\nscaler=MinMaxScaler()\ndf_green['sum'] = scaler.fit_transform(df_green[['sum']])","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import plotly.graph_objects as go\nfrom plotly.subplots import make_subplots\n\naxes = ['Air Quality','Environmental Governance','CO2','Energy','Buildings','Transport','Waste & Land use','Water']\nfig = make_subplots(rows=1, cols=1, specs=[[{'type': 'polar'}]*1]*1)\ncity_list = list(df_green.nlargest(10, ['sum'])['Organization'])\nprint(\"Double click the legend to see individual contour!\")\n\nfor c in city_list:\n    city_grade = list(df_green[df_green[\"Organization\"] == c].iloc[0,3:11])\n\n    fig.add_trace(go.Scatterpolar(\n          name = c,\n          r = city_grade + [city_grade[0]],\n          theta = axes + [axes[0]],\n        ), 1, 1)\nfig.update_traces(fill='toself')\nfig.update_layout(\n  polar=dict(\n    radialaxis=dict(\n      visible=True,\n      range=[0, 1]\n    )),\n  font_size=12,\n  legend_font_size=12,\n  template = 'presentation',\n  title = '<b>Top 10 Cities with Highest MGCI Score</b> <br><i>Double click the legend to see individual contour!</i>')\nfig.show()\n\nfig = make_subplots(rows=1, cols=1, specs=[[{'type': 'polar'}]*1]*1)\ncity_list2 = list(df_green.nsmallest(10, ['sum'])['Organization'])\nfor c in city_list2:\n    city_grade = list(df_green[df_green[\"Organization\"] == c].iloc[0,3:11])\n\n    fig.add_trace(go.Scatterpolar(\n          name = c,\n          r = city_grade + [city_grade[0]],\n          theta = axes + [axes[0]],\n        ), 1, 1)\n\nfig.update_traces(fill='toself')\nfig.update_layout(\n  polar=dict(\n    radialaxis=dict(\n      visible=True,\n      range=[0, 1]\n    )),\n  font_size=12,\n  legend_font_size=12,\n  template = 'presentation',\n  title = '<b>Top 10 Cities with Lowest MGCI Score</b> <br><i>Double click the legend to see individual contour!</i>')\n\nfig.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# emission map for all countries\nimport plotly.express as px\n\ncols = [\"Organization\",\"air_score\",\"gov_score\",\"co2_score\",\"energy_score\",\"building_score\",\\\n       \"transport_score\",\"waste_score\",\"water_score\",\"sum\"]\ndf_grade = df_green[cols].melt(id_vars=[\"Organization\"], \n        var_name=\"Score\", \n        value_name=\"Value\")\ndf_grade = pd.merge(df_grade, df_green[[\"Organization\", \"Country\"]], on = 'Organization', how='left')\n\nfig = px.choropleth(df_grade,locations=\"Country\", locationmode='country names', color=\"Value\",color_continuous_scale='Greens',\n  animation_frame=\"Score\", animation_group=\"Country\", title = '2020 Modified Green City Index KPI Metric Score Distribution <br><i>- based on features extracted from CDP survey<i>')\n\nfig.update_layout(geo=dict(\n    countrycolor= \"#444444\",\n    showcountries=True))\nfig.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"<div id=\"#3\"></div>\n<font color='#088a5a' size=5>3. Analysis on Corporate + City: CDP Answer Mining</font><br>            \n\nIn this section, we dive into the corporate survey data set and check whether there is any kind of synergy/collaborations with the city governments.\n"},{"metadata":{"trusted":true},"cell_type":"code","source":"corp_info = pd.read_csv('../input/cdp-unlocking-climate-solutions/Corporations/Corporations Disclosing/Climate Change/2020_Corporates_Disclosing_to_CDP_Climate_Change.csv')\nd = {'Organization': cc_df['organization'].unique()}\nfirm_green = pd.DataFrame(data=d)\nqs = cc_df['Question Name'].unique()\n\nmapping_country = dict(corp_info[['organization', 'country']].values)\nmapping_industry = dict(corp_info[['organization', 'primary_industry']].values)\nmapping_engage = dict(cc_df[cc_df[\"Question Name\"] == qs[5]][[\"organization\",\"Response Answer\"]].values)\nmapping_climate = dict(cc_df[cc_df[\"Question Name\"] == qs[42]][[\"organization\",\"Response Answer\"]].values)\nmapping_water = dict(cc_df[cc_df[\"Question Name\"] == qs[96]][[\"organization\",\"Response Answer\"]].values)\n\nfirm_green['Country'] = firm_green['Organization'].map(mapping_country)\nfirm_green['Industry'] = firm_green['Organization'].map(mapping_industry)\nfirm_green['engage'] = firm_green['Organization'].map(mapping_engage)\nfirm_green['engage_climate'] = firm_green['Organization'].map(mapping_climate)\nfirm_green['engage_water'] = firm_green['Organization'].map(mapping_water)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# extract quantitiative emission information\ntCO2e = cc_df.groupby('Question Name').get_group(qs[21]) # total scope 1 CO2 emission in metric tons\ntCO2e = tCO2e[(tCO2e[\"row_name\"] == 'Reporting year') & (tCO2e[\"column_number\"] == 1)]\ntCO2e.rename(columns = {'organization': 'Organization'}, inplace = True)\n# df = firm_green.copy()\nfirm_green = pd.merge(firm_green,tCO2e[['Organization','Response Answer']],on='Organization', how='left')\nfirm_green[\"Response Answer\"] = pd.to_numeric(firm_green[\"Response Answer\"], errors='coerce')\nfirm_green.rename(columns = {'Response Answer': 'totCO2'}, inplace = True)\nqs[21]","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"def recalc(df, col):\n    d = df[col].value_counts()\n    dd = {}\n    for k,v in d.items():\n        choices = [x.strip() for x in k.split(';')]\n        for choice in choices:\n            if choice in dd:\n                dd[choice] += v\n            else:\n                dd[choice] = v\n    return dd","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from collections import Counter\nfrom wordcloud import WordCloud, STOPWORDS\n\n# city vs. corporate risks\ncity_risk_q = [i[0] for i in get_q(city_df,\"risk\")]\ncity_risk_list = []\nfor q in city_risk_q:\n    city_risk_list.append(' '.join([i for i in list(get_ans(city_df, q).unique()) if type(i) == str and \\\n                                    'http' not in i and 'de' not in i and 'please' not in i]))\n\ncity_risks = ' '.join([str(elem) for elem in city_risk_list]) \n\n# city_risks = combine_ans(city_df, \"risk\")\ncorp_risks = combine_ans(cc_df, \"risk\")\nstopwords = set(STOPWORDS) \n\nfig = plt.figure()\nfig.set_size_inches(20, 10)\ncolors_set = ['royalblue', 'indianred']\nskills_list = [city_risks,corp_risks]\ntitles_list = ['City risks', 'Corporate risks']\n\nfor i in range(2):\n    ax = fig.add_subplot(1,2,i+1)\n    word_could_dict=skills_list[i]\n    # Create wordcloud object\n    wordcloud = WordCloud(width = 1200, height = 1200, background_color=\"white\", stopwords = stopwords, \n                          color_func=lambda *args, **kwargs: colors_set[i], relative_scaling = 0.5).generate(word_could_dict)\n    \n    ax.imshow(wordcloud, interpolation = 'bilinear')\n    ax.axis('off')\n\n    # Set title\n    ax.set_title(titles_list[i], size=48, pad=50)\n    \nplt.tight_layout(pad=0)\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### City + Business Collaboration: what approaches are adopted?"},{"metadata":{"trusted":true},"cell_type":"code","source":"pref_color = ['#F7819F', '#F5A9BC', '#E6E6E6', '#CEF6D8', '#9FF781']\ndds = [recalc(firm_green, \"engage_climate\"),recalc(firm_green, \"engage_water\")]\nq = [42, 96]\nfor ii,dd in enumerate(dds):\n    xx = sorted(list(dd.keys()))\n\n    # matplotlib general settings\n    fig, ax = plt.subplots(figsize=(35,1),frameon=False)\n    plt.title(\"Q\"+str(q[ii]) + \": \" + qs[q[ii]], fontsize=28, loc='left')\n    ax.get_xaxis().set_visible(False)\n    ax.tick_params(axis='y', labelsize=20, labelcolor='grey')  \n    ax.set_facecolor('white')\n    ax.axis('off')\n\n    # Draw each bar and text separately with appropriate offset\n    bar_start = 0\n    cnts = [dd[_]/np.sum(list(dd.values())) for _ in xx]\n\n    for i in range(len(dd)):\n        ax.barh(y=['All Respondents'], width=cnts[i], height=0.1, left=bar_start, color=pref_color[i])\n        plt.text(bar_start + cnts[i]/2 - 0.01, -0.01, \"{:.0%}\".format(cnts[i]), fontsize=20)\n        bar_start += cnts[i]\n\n#     Draw legend and set color of its text\n    leg = ax.legend(xx, loc=(0,-0.5), ncol=5, fontsize=18, frameon=True, facecolor='white');\n    for txt in leg.get_texts():\n        plt.setp(txt, color='grey')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from plotly.offline import init_notebook_mode, iplot\nimport matplotlib.colors as colors\n\n# recalculate to account for multiple answers\ndd1 = recalc(firm_green, \"engage\")\nxx = list(dd1.keys())\nxx = [_ + \"<br>(\" +str(round(100*dd1[_]/np.sum(list(dd1.values())),1))+ \"%)\" for _ in xx]\nyy = [\"\"]*len(dd1)\ncc = list(colors._colors_full_map.values())\n\ntrace1 = go.Scatter(x = xx, y = [\"\"]*len(dd1), mode='markers', name=\"\", marker=dict(color=cc[:len(xx)], opacity=0.4, size = 0.2*np.array(list(dd1.values()))))\nlayout = go.Layout(barmode='stack', height=380, margin=dict(l=20), title=\"Approaches of corporate engagement on climate-related issues\",\n                   legend = dict(orientation=\"h\", x=0.1, y=1.15), plot_bgcolor='#fff', paper_bgcolor='#fff', \n                   showlegend=False)\n\nfig = go.Figure(data=[trace1], layout=layout)\niplot(fig)\n\n# city engagement\ndd = get_ans(city_df, 79).value_counts()[1:10]\nxx = list(dd.keys())\nxx = [_ + \"<br>(\" +str(round(100*dd[_]/dd.values.sum()))+ \"%)\" for _ in xx]\nyy = [\"\"]*len(dd)\ncc = list(colors._colors_full_map.values())\n\ntrace1 = go.Scatter(x = xx, y = [\"\"]*len(dd), mode='markers', name=\"\", marker=dict(color=cc[:len(xx)], opacity=0.4, size = 0.2*np.array(list(dd.values))))\nlayout = go.Layout(barmode='stack', height=320, margin=dict(l=20), title=\"Approaches of city engagement with businesses\",\n                   legend = dict(orientation=\"h\", x=0.1, y=1.15), plot_bgcolor='#fff', paper_bgcolor='#fff', \n                   showlegend=False)\n\nfig = go.Figure(data=[trace1], layout=layout)\niplot(fig)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"vals = dd.values[:6]/100","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# flow chart\ncol_yes = \"#fad46b\"\ncol_no = \"#97c6e8\"\npfs = [\"  Cities\", \"  Businesses\"]\n\nroles = list(dd.keys()[1:7])\nds = [\"Collaboration\"]\n\nvals = list(dd.values[:6]/100)\n# vals = [2.71, 2.3 , 1.72, 1.58, 1.39, 1.31]\nvals2 = [1, 2.3, 1, 1.2, 0.9, 0.9]\nsums = np.array(vals) + np.array(vals2)\nvals += vals2\n\n\nfig = go.Figure(data=[go.Sankey(\n    node = dict(\n      pad = 50,\n      thickness = 10,\n      line = dict(color = \"gray\", width = 2),\n      label =  pfs +  roles + ds,\n      color = [col_yes, col_no] + [\"#6ccc86\"]*6\n    ),\n    link = dict(\n      source = [0, 1]*len(roles) + [2,3,4,5,6,7]*len(ds),\n      target = [2]*len(pfs) + [3]*len(pfs) + [4]*len(pfs) + [5]*len(pfs) + [6]*len(pfs) + [7]*len(pfs) + [8, 8, 8, 8, 8, 8],\n      value = vals + list(sums)\n  ))])\n\n\nfig.update_layout(title_text='Major city-business collaboration pathways extracted from CDP survey',font=dict(size = 12),)\nfig.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"<div id=\"#4\"></div>\n<font color='#088a5a' size=5>4. Does setting up plans/targets promote sustainability performance?</font><br>            \n\nIn this part, we aim to provide empirical evidence on the determinants of sustainability performance."},{"metadata":{"trusted":true},"cell_type":"code","source":"# CO2 emission by industry\nco2_by_industry = firm_green.groupby('Industry')['totCO2'].sum()\nco2_by_industry = dict(sorted(co2_by_industry.items(), key=lambda co2_by_industry: co2_by_industry[1])) # sorted\n\nx_pos = [i for i, _ in enumerate(co2_by_industry)]\n\nfig, ax = plt.subplots(figsize = (10,6))\nplt.barh(x_pos, co2_by_industry.values(), color='green')\nplt.ylabel(\"Industry\")\nplt.xlabel(\"CO2 Emissions (metric ton)\")\nplt.title(\"CO2 emission by industry\",backgroundcolor='#cbe7e3',fontsize = 17)\nax.set_yticks(x_pos)\nax.set_yticklabels(co2_by_industry.keys(), rotation=0)\n# plt.yticks(x_pos, x)\nax.grid(False)\nax.xaxis.grid(False)\nax.yaxis.grid(False)\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### Main Reasons for Not Having ...\n- plans\n- targets\n- assessments"},{"metadata":{"trusted":true},"cell_type":"code","source":"q = set(get_q(city_df,\"not have\")) & set(get_q(city_df,\"why\")) #| set(get_q(city_df,\"not\"))\nq = dict(q)\nq","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"The responses to the above CDP questions provide a good secondary data source to split the responders into groups with or without early planning. "},{"metadata":{"trusted":true},"cell_type":"code","source":"for k,val in q.items():\n    options = city_df.groupby('Question Name').get_group(val)[\"Response Answer\"].value_counts().keys()\n    options_map = {}\n    for i in np.arange(len(options)):\n        options_map[options[i]] = i\n\n    df_cityQ['q'+str(k)] = pd.DataFrame(city_df.groupby('Question Name').get_group(val)[\"Response Answer\"]).reset_index(drop = True)\n#     df_cityQ[k] = df_cityQ[k].map(options_map) # convert to numeric values\n\ndf_cityQ['CDP Region'] = df_cityQ['city'].map(city_region_dict)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Compare region distribution\n# city_with_planning = list(df_cityQ[df_cityQ.iloc[:, 4:10].eq(\"Question not applicable\").all(axis=1)][\"city\"])\ncity_wo_planning = list(df_cityQ[(df_cityQ.iloc[:, 4:10].eq(\"Question not applicable\")).sum(axis=1) <5][\"city\"])\ncity_wo_planning = set(city_wo_planning) | set(list(df_cityQ[(df_cityQ.iloc[:, 4:10].eq(\"Do not know\")).sum(axis=1) >= 2][\"city\"])) \ncity_with_planning = [c for c in list(df_cityQ[\"city\"]) if c not in city_wo_planning] \n\ndict_plan_city = df_cityQ[df_cityQ['city'].isin(city_with_planning)]['CDP Region'].value_counts()\ndict_all_city = df_cityQ['CDP Region'].value_counts()\nplan_cities = pd.DataFrame(dict_plan_city,index=dict_plan_city.keys())\nall_cities = pd.DataFrame(dict_all_city)\nCOLORS_SET_B_G_R = [sns.color_palette('muted')[0], sns.color_palette('muted')[2], sns.color_palette('muted')[3]]\n\nsns.set(style=\"whitegrid\")\n# Initialize the matplotlib figure\nf, ax = plt.subplots(figsize=(10, 6))\nsns.barplot(x=\"CDP Region\", y=all_cities.index, data=all_cities,\n            label=\"Total\", color=\"lightgrey\")\nsns.barplot(x=\"CDP Region\", y=plan_cities.index, data=plan_cities, \n            label=\"Citis with sustainability plans\", color=COLORS_SET_B_G_R[2], edgecolor='black')\n\n\n# Add a legend and informative axis label\nax.legend(ncol=2, loc=\"lower right\", frameon=True, prop={'size': 10})\nax.set(xlim=(0, 180), ylabel=\"\", xlabel=\"\")\n\n# Remove reduntant borders and labels\nax.xaxis.grid(False)\nax.yaxis.grid(False)\nax.xaxis.set_label_text(\"# of cities\")\nax.yaxis.set_label_text(\"CDP Region\")\nsns.despine(left=False, bottom=False)\n\n# Set title and labels size\n_ = ax.set_title('Number of Cities with Sustainable Planning across CDP surveys', fontsize=20, pad=25)\nax.tick_params(axis='y', which='major', labelsize=12)\n_ = plt.setp(fig.patches, linewidth=0.5)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"def gen_xaxis(title):\n    \"\"\"\n    Creates the X Axis layout and title\n    \"\"\"\n    xaxis = dict(\n            title=title,\n            titlefont=dict(\n                color='#AAAAAA'\n            ),\n            showgrid=False,\n            color='#AAAAAA',\n            )\n    return xaxis\n\n\ndef gen_yaxis(title):\n    \"\"\"\n    Creates the Y Axis layout and title\n    \"\"\"\n    yaxis=dict(\n            title=title,\n            titlefont=dict(\n                color='#AAAAAA'\n            ),\n            showgrid=False,\n            color='#AAAAAA',\n            )\n    return yaxis\ndef gen_layout(charttitle, xtitle, ytitle, lmarg, h, annotations=None):  \n    \"\"\"\n    Creates whole layout, with both axis, annotations, size and margin\n    \"\"\"\n    return go.Layout(title=charttitle, \n                     height=h, \n                     width=800,\n                     showlegend=False,\n                     xaxis=gen_xaxis(xtitle), \n                     yaxis=gen_yaxis(ytitle),\n                     annotations = annotations,\n                     margin=dict(l=lmarg),\n                    )\ndef gen_annotations(annot):\n    \"\"\"\n    Generates annotations to insert in the chart\n    \"\"\"\n    if annot is None:\n        return []\n    \n    annotations = []\n    # Adding labels\n    for d in annot:\n        annotations.append(dict(xref='paper', x=d['x'], y=d['y'],\n                           xanchor='left', yanchor='bottom',\n                           text= d['text'],\n                           font=dict(size=13,\n                           color=d['color']),\n                           showarrow=False))\n    return annotations","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df_cityQ[\"sustainable\"] = \"nan\"\ndf_cityQ.loc[df_cityQ[\"city\"].isin(city_wo_planning),\"sustainable\"] = False\ndf_cityQ.loc[df_cityQ[\"city\"].isin(city_with_planning),\"sustainable\"] = True\ndf_green2 = pd.merge(df_green, df_cityQ[['city','sustainable']],left_on='Organization', right_on='city', how='left') \n\nx0 = df_green2[df_green2[\"sustainable\"] == False][\"sum\"]\nx1 = df_green2[df_green2[\"sustainable\"] == True][\"sum\"]\n\n# df2 = pd.merge(df,df_cityQ[['city','sustainable']],left_on='Organization', right_on='city', how='left') \n# x0 = df2[df2[\"sustainable\"] == False][\"totalCO2e\"]\n# x1 = df2[df2[\"sustainable\"] == True][\"totalCO2e\"]\n\nuneco_cities = go.Histogram(\n    x=x0,\n    opacity=0.5,\n    marker={'color': 'lightgray'},\n)\neco_cities = go.Histogram(\n    x=x1,\n    opacity=0.5,\n    marker={'color': 'mediumaquamarine'},\n)\n\nannot_dict = [{'x': 0.2, 'y': 67, 'text': 'The less \"sustainable\" cities tend to get lower scores','color': 'gray'},\n              {'x': 0.6, 'y': 25, 'text': '\"Sustainable\" city group tends to have<br>higher scores','color': 'mediumaquamarine'}]\n\nlayout = gen_layout('<b>Distribution of MGCI Scores of City Groups</b><br><i>Based on sustainable planning activities and risk awareness and/or preparations</i>', \n                    'Modified Green City Index (MGCI) Score',\n                    'Quantity of Respondents',\n                    annotations=gen_annotations(annot_dict),\n                    lmarg=120, h=500\n                    )\nlayout['barmode'] = 'overlay'\n\ndata = [uneco_cities, eco_cities]\nlayout = go.Layout(layout)\nfig = go.Figure(data=data, layout=layout)\n\niplot(fig)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Comparisons between cities with and without sustainable planning\nfig, ax = plt.subplots(figsize=(5, 5))\nCOLORS_SET_B_G_R = [sns.color_palette('muted')[0], sns.color_palette('muted')[2], sns.color_palette('muted')[3]]\n\ng = sns.barplot(x=\"sustainable\", y=\"sum\",\n                data=df_green2, palette=COLORS_SET_B_G_R[1:3],\n                dodge=True, ci=90, capsize=0.1, errwidth =1, edgecolor='black')\n\n# Remove redundant labels and borders\nsns.despine(left=False, bottom=False)\nax.xaxis.grid(False)\nax.yaxis.grid(False)\nax.xaxis.set_label_text(\"\")\nax.yaxis.set_label_text(\"\")\n# Set title\n_ = ax.set_title('Average MGCI Scores for City Groups', fontsize=20, pad=25)\n# Set x ticks\nax.tick_params(axis='x', which='major', labelsize=12)\n_ = ax.xaxis.set_ticklabels([\"Sustainable\", \"non-Sustainable\"])\n_ = plt.setp(g.patches, linewidth=0.5) ","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### Clustering based on effects: Decision Trees"},{"metadata":{"trusted":true},"cell_type":"code","source":"# let us fit a decision tree\nfrom sklearn.tree import DecisionTreeRegressor\ndt = DecisionTreeRegressor(max_leaf_nodes=7, min_samples_leaf=5)\ndt.fit(df_green2[df_green2.columns[3:11]], df_green2[\"sustainable\"])\n\n# let us plot a decision tree\nimport graphviz \nfrom sklearn import tree\ndot_data = tree.export_graphviz(dt, out_file=None, \n                                feature_names=df_green2.columns[3:11],  \n                                filled=True, rounded=True,  \n                                special_characters=True)  \ngraph = graphviz.Source(dot_data)  \ngraph ","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"\nfig = go.Figure(data = [go.Bar(\n            x=dt.feature_importances_[np.argsort(dt.feature_importances_)],\n            y=list(df_green2.columns[3:11][np.argsort(dt.feature_importances_)]),\n            orientation='h', marker=dict(color=COLORS_SET_B_G_R, opacity=0.1))], \n               layout = go.Layout(title=\"MGCI Axis Importances to Sustainable Preparedness\", plot_bgcolor='#fff', paper_bgcolor='#fff',  margin=dict(l=100),\n                               width=900, height=500, legend=dict(orientation=\"h\", x=0.1, y=1.1)))\nfig.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### Summarize the reasons"},{"metadata":{},"cell_type":"markdown","source":"Let's take a brief look at why planning/assessments were not implemented."},{"metadata":{"trusted":true},"cell_type":"code","source":"import bs4 as bs\nimport urllib.request\nimport re\nimport nltk\nimport heapq\n\nexcuses = combine_ans(city_df[city_df['Country'] == \"United States of America\"], [\"why\",\"not have\"])\narticle_text = excuses\n\n# Removing Square Brackets and Extra Spaces\narticle_text = re.sub(r'\\[[0-9]*\\]', ' ', article_text)\narticle_text = re.sub(r'\\s+', ' ', article_text)\n\n# Removing special characters and digits\nformatted_article_text = re.sub('[^a-zA-Z]', ' ', article_text )\nformatted_article_text = re.sub(r'\\s+', ' ', formatted_article_text)\nsentence_list = nltk.sent_tokenize(article_text)\nstopwords = nltk.corpus.stopwords.words('english')\n\nword_frequencies = {}\nfor word in nltk.word_tokenize(formatted_article_text):\n    if word not in stopwords:\n        if word not in word_frequencies.keys():\n            word_frequencies[word] = 1\n        else:\n            word_frequencies[word] += 1\n    maximum_frequncy = max(word_frequencies.values())\n    \nfor word in word_frequencies.keys():\n    word_frequencies[word] = (word_frequencies[word]/maximum_frequncy)\n    sentence_scores = {}\n    \nfor sent in sentence_list:\n    for word in nltk.word_tokenize(sent.lower()):\n        if word in word_frequencies.keys():\n            if len(sent.split(' ')) < 30:\n                if sent not in sentence_scores.keys():\n                    sentence_scores[sent] = word_frequencies[word]\n                else:\n                    sentence_scores[sent] += word_frequencies[word]\n                    \nsummary_sentences = heapq.nlargest(10, sentence_scores, key=sentence_scores.get)\n\nsummary_sentences[0] = '- ' + summary_sentences[0] \nsummary = '\\n- '.join(summary_sentences)\n\nprint('\\033[1m' + \"Summary for reasons not planning for sustainability:\" + '\\033[0m')\nprint(summary)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"<div id=\"#5\"></div>\n<font color='#088a5a' size=5>5. Concluding Remarks: Actionable Insights</font><br>            \n\n\nClimate change and water stress is a present risk to business and cities alike.These environmental changes can give rise to many uncertainties and it is management’s responsibility to consider these uncertainties and how best to respond to them. Companies are increasingly expected to provide information and make relevant disclosures. \n <br>\n \nOur analysis draws upon the Green City Index framework and NLP analytics to construct a meaningful KPI for city development and to understand whether sustainability performance is driven by planning and preparedness. In extending the use of the generic approaches in this analysis, important policy implications could be derived. \n <br>\n\nOverall, the results from this exploratory imply two important insights:\n\n**- Going Beyond Climate Change Risk Management**\n <br>\n \nWhilst a growing number of firms start to take a more proactive stance on climate change, many firms are still adopting a \"wait-and-see\" approach. Our quantitative analyses show that greater awareness and preparedness is what sets superior performers apart. Qualitative content analysis confirm that superior performers provide more detailed description of climate change strategies that go beyond managing climate change risks. The results also support the importance of \"command-and-control\" legislations particularly for poor sustainability performers who are likely to react when environmental/social issues are perceived as a real threat through mandatory sanctions.\n <br> \n\n**- Seeking collaborative opportunities is exceedingly helpful**\n <br> \n\n In the context of this study,  it is essential to prompt more companies to proactively seek innovative opportunities together with local government to address the challenges brought about by climate change. Voluntary proactive collaborations between business entities and governments could significantly boost sustainability performance.\n \n  <br> \nThe findings from this study, however, are subject to a numberof limitations. Data constraints may limit the validity of some variables. It is also important to acknowledge the inherent limitations of empirical analysis to capture the complexity of numerous dimensions included. Despite these constraints, the insights gathered from here can be useful as a springboard for future in-depth studies. "},{"metadata":{},"cell_type":"markdown","source":"<div id=\"#6\"></div>\n<font color='#088a5a' size=5>6. References</font><br>     \n\n1. Summers, J. Kevin, et al. \"Conceptualizing holistic community resilience to climate events: Foundation for a climate resilience screening index.\" GeoHealth 1.4 (2017): 151-164.\n2. Dietz, Simon, et al. \"An assessment of climate action by high-carbon global corporations.\" Nature Climate Change 8.12 (2018): 1072-1075.\n3. Elijido-Ten, Evangeline O. \"Does recognition of climate change related risks and opportunities determine sustainability performance?.\" Journal of cleaner production 141 (2017): 956-966.\n\nCredits to [Teresa Kubacka](https://www.kaggle.com/tkubacka/a-story-told-through-a-heatmap) and [Shivam Bansal](https://www.kaggle.com/shivamb/spending-for-ms-in-data-science-worth-it) for awesome visualization ideas!"}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4}