How to reorder the days of week in this Pandas Pivot Table?-CodePudding

import numpy as np 
import pandas as pd 
import matplotlib.pyplot as plt
import seaborn as sns
import datetime
    
df = pd.read_excel("Baltimore Towing Division.xlsx",sheet_name="TowingData")

df['Month'] = pd.DatetimeIndex(df['TowedDate']).strftime("%b")
df['Week day'] = pd.DatetimeIndex(df['TowedDate']).strftime("%a")


monthOrder = ['Jan', 'Feb', 'Mar', 'Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']
dayOrder = ['Mon','Tue','Wed','Thu','Fri','Sat','Sun']


Pivotdf = pd.pivot_table(df, index=['Month'],
                        values=['TowedDate'],
                        columns=['Week day'],
                        fill_value=0,
                        aggfunc='count').reindex(monthOrder,axis=0).reindex(dayOrder,axis=1)

print(df)

I use the .reindex function at the end of the pivot table for reindex the Months and the columns 'Week day', it returns a NaN in the results.

Using .reindex in axis=1

Not doing the .reindex at the column of the days the Pivot table brings me the results, but with the days of the week disorganized. I need them to appear in the table in order like this: Mon, Tue, Wed, Thu, Fri, Sat, Sun

Whitout using .reindex in axis=1

CodePudding user response：

Maybe using loc:

# with values=['TowedDate'] -> MultiIndex
Pivotdf = pd.pivot_table(df, index=['Month'],
                        values=['TowedDate'],
                        columns=['Week day'],
                        fill_value=0,
                        aggfunc='count').loc[monthOrder, (slice(None), dayOrder)]

# OR

# with values='TowedDate' -> Index
Pivotdf = pd.pivot_table(df, index=['Month'],
                        values='TowedDate',
                        columns=['Week day'],
                        fill_value=0,
                        aggfunc='count').loc[monthOrder, dayOrder)]

Output:

>>> Pivotdf
         TowedDate                        
Week day       Mon Tue Wed Thu Fri Sat Sun
Month                                     
Jan              1   0   1   0   1   0   0
Feb              2   0   1   0   1   0   0
Mar              1   0   0   0   0   0   0
Apr              0   0   0   1   0   1   0
May              0   1   1   3   1   1   2
Jun              1   0   0   0   0   1   2
Jul              0   1   0   0   2   0   0
Aug              3   0   0   0   1   2   1
Sep              0   0   1   1   0   1   0
Oct              3   0   0   0   1   0   1
Nov              1   0   0   0   1   2   3
Dec              0   1   1   0   0   0   0

CodePudding user response：

Corralien's method solved the problem.

# with values=['TowedDate'] -> MultiIndex
Pivotdf = pd.pivot_table(df, index=['Month'],
                        values=['TowedDate'],
                        columns=['Week day'],
                        fill_value=0,
                        aggfunc='count').loc[monthOrder, (slice(None), dayOrder)]

Millions of thanks to all the members who answered and assisted me in this question