Saturday, March 30, 2019

Script to analyze personal trip data exported from Grab

Script to analyze personal trip data exported from Grab:


import pandas as pd
import numpy as np

df = pd.read_csv('/Users/donghua/Documents/Grab-history-20180-201903.csv',skiprows=3,skipfooter=3,engine='python')
# df.head(1)
df['Date']=pd.to_datetime(df['Date'], format='%a %d %b %Y, %I:%M:%S %p')
df['Month']=df['Date'].dt.strftime('%Y-%m')
# df.head(1)

df[['Month','Fare']].groupby('Month').sum().sort_index()
df[['Month','Fare']].groupby('Month').mean().sort_index()

import matplotlib.pyplot as plt
get_ipython().run_line_magic('matplotlib', 'inline')
df[['Month','Fare']].groupby('Month').sum().plot.bar();
df[['Month','Fare']].groupby('Month').mean().plot.bar();
Jupyter Notebook Output:
import pandas as pd
import numpy as np
df = pd.read_csv('/Users/donghua/Documents/Grab-history-20180-201903.csv',skiprows=3,skipfooter=3,engine='python')
# df.head(1)
df['Date']=pd.to_datetime(df['Date'], format='%a %d %b %Y, %I:%M:%S %p')
df['Month']=df['Date'].dt.strftime('%Y-%m')
# df.head(1)
df[['Month','Fare']].groupby('Month').sum().sort_index()

df[['Month','Fare']].groupby('Month').mean().sort_index()


import matplotlib.pyplot as plt
%matplotlib inline
df[['Month','Fare']].groupby('Month').sum().plot.bar();
df[['Month','Fare']].groupby('Month').mean().plot.bar();

1 comment:

  1. It's about the information. However we pursue the instruments driving the information.
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