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

Question

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

Answer 1

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

Answer 2

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