{"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_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"![](https://storage.googleapis.com/kaggle-competitions/kaggle/37644/logos/header.png?t=2022-08-05-15-26-16)","metadata":{}},{"cell_type":"markdown","source":"* Let's Start with the Required Libraries","metadata":{}},{"cell_type":"code","source":"import gc\nimport numpy as np\nimport pandas as pd\n\nimport seaborn as sns\nimport plotly.express as px\nimport plotly.graph_objects as go\n\nfrom plotly.subplots import make_subplots","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2022-10-16T12:56:18.945529Z","iopub.execute_input":"2022-10-16T12:56:18.946311Z","iopub.status.idle":"2022-10-16T12:56:20.466932Z","shell.execute_reply.started":"2022-10-16T12:56:18.946219Z","shell.execute_reply":"2022-10-16T12:56:20.465886Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"**File descriptions**\n\n> **nyra_start_table.csv** - horse/jockey race data\n\n> **nyra_race_table.csv** - racetrack race data\n\n> **nyra_tracking_table.csv** - tracking data\n\n> **nyra_2019_complete.csv** - combined table of three above files","metadata":{}},{"cell_type":"markdown","source":"nyra_2019_complete.csv - This file is the combined 3 files into one table. ","metadata":{}},{"cell_type":"markdown","source":"# <div style=\"color:white; display:fill;  border-radius:5px;font-size:200%;font-family:Verdana;letter-spacing:0.5px; \"><center> <p style=\"background-image:url('https://storage.googleapis.com/kaggle-competitions/kaggle/37644/logos/thumb76_76.png?t=2022-08-05-15-26-09'); background-repeat:no-repeat; background-attachment:left; background-position:left; background-size:90px 90px; padding: 10px; color:#F70000; text-align:center;\"> Preparing Data</p></center> </div>","metadata":{}},{"cell_type":"markdown","source":"**nyra_start_table.csv**\n\n**track_id** - 3 character id for the track the race took place at. AQU -Aqueduct, BEL - Belmont, SAR - Saratoga.\n\n**race_date** - date the race took place. YYYY-MM-DD.\n\n**race_number** - Number of the race. Passed as 3 characters but can be cast or converted to int for this data set.\n\n**program_number** - Program number of the horse in the race passed as 3 characters. Should remain 3 characters as it isn't limited to just numbers. Is \nessentially the unique identifier of the horse in the race.\n\n**weight_carried** - An integer of the weight carried by the horse in the race.\n\n**jockey** - Name of the jockey on the horse in the race. 50 character max.\n\n**odds** - Odds to win the race passed as an integer. Divide by 100 to derive the odds to 1. Example - 1280 would be 12.8-1.\n\n**position_at_finish** - An integer of the horse's finishing position. (added to the dataset 9/8/22)","metadata":{}},{"cell_type":"markdown","source":"* Fixing the Columns Names alongside","metadata":{}},{"cell_type":"code","source":"nyra_start = pd.read_csv('../input/big-data-derby-2022/nyra_start_table.csv')\nnyra_start.columns = ['track_id', 'race_date', 'race_number', 'program_number', 'weight_carried', 'jockey', 'odds', 'position_at_finish']\nnyra_start['race_date'] = pd.to_datetime(nyra_start['race_date'])\nnyra_start.head()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:56:20.473404Z","iopub.execute_input":"2022-10-16T12:56:20.474430Z","iopub.status.idle":"2022-10-16T12:56:20.512936Z","shell.execute_reply.started":"2022-10-16T12:56:20.474391Z","shell.execute_reply":"2022-10-16T12:56:20.511876Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"nyra_start.info()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:56:20.514321Z","iopub.execute_input":"2022-10-16T12:56:20.514796Z","iopub.status.idle":"2022-10-16T12:56:20.531411Z","shell.execute_reply.started":"2022-10-16T12:56:20.514757Z","shell.execute_reply":"2022-10-16T12:56:20.529981Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"nyra_race = pd.read_csv('../input/big-data-derby-2022/nyra_race_table.csv',\n                       dtype={'race_number':'int8', 'distance_id':'int32',\n                              'purse':'float32'}, parse_dates=['race_date'])\nnyra_race.info()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:56:20.534578Z","iopub.execute_input":"2022-10-16T12:56:20.535004Z","iopub.status.idle":"2022-10-16T12:56:20.556804Z","shell.execute_reply.started":"2022-10-16T12:56:20.534961Z","shell.execute_reply":"2022-10-16T12:56:20.555731Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"nyra_tracking = pd.read_csv('../input/big-data-derby-2022/nyra_tracking_table.csv',\n                           parse_dates=['race_date'], dtype={'race_number':'int8'},\n                           )\nnyra_tracking.head()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:56:20.558575Z","iopub.execute_input":"2022-10-16T12:56:20.559217Z","iopub.status.idle":"2022-10-16T12:56:24.630198Z","shell.execute_reply.started":"2022-10-16T12:56:20.559177Z","shell.execute_reply":"2022-10-16T12:56:24.629078Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"nyra_tracking.info()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:56:24.631824Z","iopub.execute_input":"2022-10-16T12:56:24.632293Z","iopub.status.idle":"2022-10-16T12:56:24.643221Z","shell.execute_reply.started":"2022-10-16T12:56:24.632246Z","shell.execute_reply":"2022-10-16T12:56:24.641890Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"nyra_complete_cols = ['track_id', 'race_date', 'race_number', 'program_number', 'trackus_index', \n                         'latitude', 'longitude', 'distance_id', 'course_type', 'track_condition', \n                         'run_up_distance', 'race_type', 'purse', 'post_time', \n                         'weight_carried', 'jockey', 'odds', 'position_at_finish']\n\n\nnyra_complete = pd.read_csv('../input/big-data-derby-2022/nyra_2019_complete.csv',\n                            names=nyra_complete_cols, header=None, \n                            dtype={'race_number':'int8', \n                                   'trackus_index':'int16', 'distance_id':'int16',\n                                   'run_up_distance':'int16', 'post_time':'int16',\n                                   'weight_carried':'uint8', 'purse':'int32',\n                                  },\n                            parse_dates=['race_date'])\nnyra_complete.head()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:56:24.644731Z","iopub.execute_input":"2022-10-16T12:56:24.645888Z","iopub.status.idle":"2022-10-16T12:56:32.808077Z","shell.execute_reply.started":"2022-10-16T12:56:24.645851Z","shell.execute_reply":"2022-10-16T12:56:32.807074Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"nyra_complete.info()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:56:40.135172Z","iopub.execute_input":"2022-10-16T12:56:40.135565Z","iopub.status.idle":"2022-10-16T12:56:40.147442Z","shell.execute_reply.started":"2022-10-16T12:56:40.135531Z","shell.execute_reply":"2022-10-16T12:56:40.146239Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"nyra_complete.describe().round(1).style.background_gradient()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:56:40.708119Z","iopub.execute_input":"2022-10-16T12:56:40.708501Z","iopub.status.idle":"2022-10-16T12:56:41.957475Z","shell.execute_reply.started":"2022-10-16T12:56:40.708467Z","shell.execute_reply":"2022-10-16T12:56:41.956403Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(\"\\033[1;32;32m Rows in Dataframe ==> \\033[01m {}\\033[0;0m\".format(len(nyra_complete)))\nprint(\"\\033[1;32;32m Columns in DataFrame ==> \\033[01m {}\\033[0;0m\".format(len(nyra_complete.columns)))\nnyra_complete.isna().sum()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:56:41.959296Z","iopub.execute_input":"2022-10-16T12:56:41.960983Z","iopub.status.idle":"2022-10-16T12:56:43.017961Z","shell.execute_reply.started":"2022-10-16T12:56:41.960940Z","shell.execute_reply":"2022-10-16T12:56:43.017014Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"nyra_complete.nunique()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:56:43.019918Z","iopub.execute_input":"2022-10-16T12:56:43.020315Z","iopub.status.idle":"2022-10-16T12:56:46.769488Z","shell.execute_reply.started":"2022-10-16T12:56:43.020276Z","shell.execute_reply":"2022-10-16T12:56:46.768602Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Let's Understand Terms","metadata":{}},{"cell_type":"markdown","source":"**Track id**\n> Track id is the place or name of place where race took place.\n\n**Race Date**\n> Date of race\n\n**Race Number** \n> There are n number of races happens on the same ground, Race number is ith race.\n\n**Program Number**\n> A program number is the number each horse wears on its saddlecloth. It’s the number that appears alongside the name of each horse\n\n**Weight Carried**\n> Weight carried by the horse in the race\n\n**Jockey**\n> Name of the person who rides horse\n\n**Odds**\n> The return expected to get if the horse you bet on is successfull\n\n**Position at Finish**\n> Horse Finishing position in the race.\n\n**Latitude & Longitude**\n> Lattitude & Longitude of the horse in the race.\n\n**Trackus_index**\n> Trakus is a real-time tracking system that determines the exact location of each horse throughout a race. Collected every 0.25 seconds\n\n**Distance_id**\n> Distance of the race in furlongs (measurment unit)\n\n**Run up distance**\n> Run-up is the distance from where the gate is placed and the timing of the race begins.\n\n**Post time**\n> Time of day the race began passed as 5 character.","metadata":{}},{"cell_type":"markdown","source":"# <div style=\"color:white; display:fill;  border-radius:5px;font-size:200%;font-family:Verdana;letter-spacing:0.5px; \"><center> <p style=\"background-image:url('https://storage.googleapis.com/kaggle-competitions/kaggle/37644/logos/thumb76_76.png?t=2022-08-05-15-26-09'); background-repeat:no-repeat; background-attachment:left; background-position:left; background-size:90px 90px; padding: 10px; color:#F70000; text-align:center;\"> Exploratory Data Analysis</p></center> </div>","metadata":{}},{"cell_type":"code","source":"temp = dict(layout=go.Layout(font=dict(family='Times New Roman', size=13), width=800))\nthemes = [\"plotly\", \"plotly_white\", \"plotly_dark\", \"ggplot2\", \"seaborn\", \"simple_white\", \"none\"]","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:56:51.909342Z","iopub.execute_input":"2022-10-16T12:56:51.909735Z","iopub.status.idle":"2022-10-16T12:56:51.922294Z","shell.execute_reply.started":"2022-10-16T12:56:51.909697Z","shell.execute_reply":"2022-10-16T12:56:51.921311Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"**Univariate & Multivariate Analysis of Nyra Start table**","metadata":{}},{"cell_type":"code","source":"fig = px.bar(nyra_start, x='track_id')\nfig.update_layout(template=themes[-1], width=800,\n                title='Track ID Distribution',)\nfig.show()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:56:52.483728Z","iopub.execute_input":"2022-10-16T12:56:52.484457Z","iopub.status.idle":"2022-10-16T12:56:52.794454Z","shell.execute_reply.started":"2022-10-16T12:56:52.484416Z","shell.execute_reply":"2022-10-16T12:56:52.793465Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig = px.histogram(nyra_start, x='race_date', color='track_id',)\nfig.update_layout(template=themes[1], width=800, font=dict(family='Times New Roman', size=15),\n                  title='Count plot of Dates for Nyra Start',\n                  hovermode='x unified')\nfig.show()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:56:52.795946Z","iopub.execute_input":"2022-10-16T12:56:52.796835Z","iopub.status.idle":"2022-10-16T12:56:53.168557Z","shell.execute_reply.started":"2022-10-16T12:56:52.796794Z","shell.execute_reply":"2022-10-16T12:56:53.167567Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig = px.histogram(nyra_race, x='race_date', color='track_id')\nfig.update_layout(template=themes[1], width=800, font=dict(family='Times New Roman', size=15),\n                  title='Count plot of Dates for Nyra Race',\n                  hovermode='x unified')\nfig.show()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:56:53.170362Z","iopub.execute_input":"2022-10-16T12:56:53.176488Z","iopub.status.idle":"2022-10-16T12:56:53.294532Z","shell.execute_reply.started":"2022-10-16T12:56:53.176446Z","shell.execute_reply":"2022-10-16T12:56:53.293614Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"**The Count Plot of Date distribution show a lot of difference between the two csv files visualized above.**","metadata":{}},{"cell_type":"code","source":"def showBoxPlot(df):\n    fig = px.box(df, y='race_number', color='track_id', points='all', template=temp)\n    fig.update_layout(template=themes[0], width=800, \n                      title='Race Number Distribution',\n                     hovermode='x unified')\n    fig.show()\n    \n    fig = px.box(df, y='program_number', color='track_id', points='all' )\n    fig.update_layout(template=themes[0], width=800, \n                      title='Program Number Distribution',\n                     hovermode='x')\n    fig.show()\n    \n    fig = px.box(nyra_start, y='weight_carried', color='track_id', points='all',)\n    fig.update_layout(template=themes[0], width=800, \n                      title='Weight Carried Distribution',\n                     hovermode='x unified')\n    fig.show()\n    \n    fig = px.box(nyra_start, y='position_at_finish', color='track_id',  )\n    fig.update_layout(template=themes[0], width=800, \n                      title='Position at Finish',\n                     hovermode='x unified')\n    fig.show()\n    \n    \n\nshowBoxPlot(nyra_start)","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:56:54.501287Z","iopub.execute_input":"2022-10-16T12:56:54.502097Z","iopub.status.idle":"2022-10-16T12:56:54.838431Z","shell.execute_reply.started":"2022-10-16T12:56:54.502054Z","shell.execute_reply":"2022-10-16T12:56:54.837316Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"colors = [\"#FFFFFF\", \"#6CD4FF\", \"#F7DF00\", \"#E60000\"]\nfig = px.scatter(nyra_start, x='weight_carried', y='odds', \n                 color='track_id',\n                color_continuous_scale=colors, range_color=(0, 99, 99))\nfig.update_traces(marker=dict(size=8, symbol='circle'))\nfig.update_layout(template=themes[2], width=800, height=400,\n                 title='Odds return v/s Weights Carried', \n                 hovermode='x unified')\nfig.show()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:57:06.222524Z","iopub.execute_input":"2022-10-16T12:57:06.222929Z","iopub.status.idle":"2022-10-16T12:57:06.317609Z","shell.execute_reply.started":"2022-10-16T12:57:06.222893Z","shell.execute_reply":"2022-10-16T12:57:06.316477Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def Jockey_Plot(df):\n    fig = px.bar(df.loc[df['track_id']=='AQU'], x='jockey')\n    fig.update_layout(template=themes[-1], width=800, \n                      title='AQU Jockey Names',\n                     hovermode='x unified')\n    fig.show()\n    \n    fig = px.bar(df.loc[df['track_id']=='BEL'], x='jockey')\n    fig.update_layout(template=themes[-1], width=800, \n                      title='BEL Jockey Names',\n                     hovermode='x unified')\n    fig.show()\n    \n    fig = px.bar(df.loc[df['track_id']=='SAR'], x='jockey',  )\n    fig.update_layout(template=themes[-1], width=800, \n                      title='SAR Jockey Names',\n                     hovermode='x unified')\n    fig.show()\n    \n    \nJockey_Plot(nyra_start)\n","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:57:07.113473Z","iopub.execute_input":"2022-10-16T12:57:07.113888Z","iopub.status.idle":"2022-10-16T12:57:07.313677Z","shell.execute_reply.started":"2022-10-16T12:57:07.113850Z","shell.execute_reply":"2022-10-16T12:57:07.312598Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig = px.scatter(nyra_start, y='odds', color='track_id')\nfig.update_layout(template=themes[2], width=800, \n                  title='Odds Returns at 3 tracks',\n                 hovermode='y unified')\nfig.show()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:57:22.330364Z","iopub.execute_input":"2022-10-16T12:57:22.330782Z","iopub.status.idle":"2022-10-16T12:57:22.413105Z","shell.execute_reply.started":"2022-10-16T12:57:22.330744Z","shell.execute_reply":"2022-10-16T12:57:22.411903Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"nyra_race.head()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:57:28.955777Z","iopub.execute_input":"2022-10-16T12:57:28.956157Z","iopub.status.idle":"2022-10-16T12:57:28.973449Z","shell.execute_reply.started":"2022-10-16T12:57:28.956124Z","shell.execute_reply":"2022-10-16T12:57:28.972348Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"nyra_race.info()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:57:29.154240Z","iopub.execute_input":"2022-10-16T12:57:29.154635Z","iopub.status.idle":"2022-10-16T12:57:29.170582Z","shell.execute_reply.started":"2022-10-16T12:57:29.154601Z","shell.execute_reply":"2022-10-16T12:57:29.169186Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig = px.box(nyra_race, y='distance_id', color='track_id', points='all',\n           labels={'distance_id':'Distance'} )\nfig.update_layout(template=themes[0], width=800, \n                  title='Distance distribution',\n                 hovermode='x unified')\nfig.show()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:58:06.825477Z","iopub.execute_input":"2022-10-16T12:58:06.825922Z","iopub.status.idle":"2022-10-16T12:58:06.901260Z","shell.execute_reply.started":"2022-10-16T12:58:06.825886Z","shell.execute_reply":"2022-10-16T12:58:06.900160Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig = px.box(nyra_race, y='run_up_distance', color='track_id', \n           labels={'run_up_distance':'Run up Distance'} )\nfig.update_layout(template=themes[0], width=800, height=500,\n                  title='Run up distance distribution',\n                 hovermode='x unified')\nfig.show()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T12:59:25.300787Z","iopub.execute_input":"2022-10-16T12:59:25.301857Z","iopub.status.idle":"2022-10-16T12:59:25.381234Z","shell.execute_reply.started":"2022-10-16T12:59:25.301804Z","shell.execute_reply":"2022-10-16T12:59:25.380021Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig = px.box(nyra_race, y='purse', color='track_id',)\nfig.update_layout(template=themes[0], width=800, height=500,\n                  title='Purse distribution',\n                 hovermode='x unified')\nfig.show()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T13:12:27.365432Z","iopub.execute_input":"2022-10-16T13:12:27.365833Z","iopub.status.idle":"2022-10-16T13:12:27.440363Z","shell.execute_reply.started":"2022-10-16T13:12:27.365797Z","shell.execute_reply":"2022-10-16T13:12:27.439439Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig = px.box(nyra_race, y='post_time', color='track_id',)\nfig.update_layout(template=themes[0], width=800, height=500,\n                  title='Post time distribution',\n                 hovermode='x unified')\nfig.show()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T13:12:54.853532Z","iopub.execute_input":"2022-10-16T13:12:54.854198Z","iopub.status.idle":"2022-10-16T13:12:54.928767Z","shell.execute_reply.started":"2022-10-16T13:12:54.854160Z","shell.execute_reply":"2022-10-16T13:12:54.927723Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig = px.bar(nyra_race, x='course_type', color='track_id')\nfig.update_layout(template=themes[-1], width=800, height=400,\n                title='Course type Distribution',)\nfig.show()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T13:13:26.489357Z","iopub.execute_input":"2022-10-16T13:13:26.489744Z","iopub.status.idle":"2022-10-16T13:13:26.557228Z","shell.execute_reply.started":"2022-10-16T13:13:26.489705Z","shell.execute_reply":"2022-10-16T13:13:26.556204Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig = px.bar(nyra_race, x='track_condition', color='track_id')\nfig.update_layout(template=themes[-1], width=800, height=400,\n                title='Track Condition Distribution',)\nfig.show()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T13:13:29.516297Z","iopub.execute_input":"2022-10-16T13:13:29.516650Z","iopub.status.idle":"2022-10-16T13:13:29.584440Z","shell.execute_reply.started":"2022-10-16T13:13:29.516618Z","shell.execute_reply":"2022-10-16T13:13:29.583400Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"ig = px.bar(nyra_race, x='race_type', color='track_id')\nfig.update_layout(template=themes[-1], width=800, height=400,\n                title='Race type Distribution',)\nfig.show()","metadata":{"execution":{"iopub.status.busy":"2022-10-16T13:13:29.798207Z","iopub.execute_input":"2022-10-16T13:13:29.798804Z","iopub.status.idle":"2022-10-16T13:13:29.865361Z","shell.execute_reply.started":"2022-10-16T13:13:29.798764Z","shell.execute_reply":"2022-10-16T13:13:29.864487Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Work in Progress 🚧","metadata":{}}]}