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license: gpl-3.0 |
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Year | Model | Price | Mileage | Dealer | City | State | Transfer Fee | Stock # | |
---|---|---|---|---|---|---|---|---|---|
2013 | S | 7998 | 53 | Pleasanton | Pleasanton | CA | 949 | 16298916 | |
2011 | SL | 7998 | 83 | West Sahara | Las Vegas | NV | 799 | 16260846 | |
2011 | SL | 7998 | 71 | Ontario | Los Angeles | CA | 949 | 16287068 | |
2011 | SL | 8599 | 44 | Serramonte | San Francisco | CA | 949 | 15868010 | |
2011 | SL | 8599 | 43 | Clackamas | Clackamas | OR | 999 | 16338496 | |
2011 | SL | 8599 | 48 | LAX | Los Angeles | CA | 949 | 16529550 | |
2012 | SV | 8599 | 60 | Henderson | Las Vegas | NV | 799 | 16260281 | |
2011 | SV | 8599 | 50 | Sacramento/Roseville | Roseville | CA | 949 | 16298061 | |
2012 | SL | 8998 | 54 | Henderson | Las Vegas | NV | 799 | 16111897 |
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import pandas as pd | |
import matplotlib.pyplot as plt | |
# Import Data | |
data = pd.read_csv('scrubbed.csv') | |
data.head() | |
#Prepare "shapes" column for donut plot entry | |
shapes = data['shape'].value_counts(normalize=True) * 100 | |
Keys = shapes.keys().to_list() |
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# conda create -n pd python | |
# (source) conda activate pd | |
# conda install pandas | |
# conda install matplotlib | |
# remove pd environment | |
import json | |
import os | |
import datetime as dt | |
import pandas as pd |
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