In this post, we will see how to convert a Pandas pivot table to a regular DataFrame.
To convert pivot table to DataFrame we can use:
(1) the reset_index()
method
df_p.set_axis(df_p.columns.tolist(), axis=1).reset_index()
(2) to_records() + pd.DataFrame()
pd.DataFrame(df_p.to_records())
Let's cover both ways in detail in the next sections.
Setup
First, let's create the DataFrame with 4 columns:
import pandas as pd
import numpy as np
data = {'date': np.random.choice([202303, 202304], size=100),
'code': np.random.choice([*'ABC'], size=100),
'type': np.random.choice([*'RB'], size=100),
'val': np.arange(100)}
df = pd.DataFrame(data)
df
First 5 rows of this DataFrame are:
date | code | type | val | |
---|---|---|---|---|
0 | 202304 | B | B | 0 |
1 | 202304 | A | B | 1 |
2 | 202304 | B | B | 2 |
3 | 202303 | C | B | 3 |
4 | 202304 | A | B | 4 |
We can create pivot table from above data by:
df_p = df.pivot_table(index=['date','code'], columns='type', values='val', aggfunc="count")
df_p
result:
type | B | R | |
---|---|---|---|
date | code | ||
202303 | A | 9 | 5 |
B | 9 | 10 | |
C | 11 | 12 | |
202304 | A | 11 | 6 |
B | 10 | 4 | |
C | 6 | 7 |
Let's see how to convert the pivot table back to normal DataFrame. Essentially this means to remove the MultiIndex or flatten the DataFrame.
reset_index()
To convert pivot table to a normal DataFrame in Pandas, we can combine:
reset_index()
methodset_axis()
We can flatten the pivot table by removing the MultiIndex:
df_p.set_axis(df_p.columns.tolist(), axis=1).reset_index()
The result is:
date | code | B | R | |
---|---|---|---|---|
0 | 202303 | A | 9 | 5 |
1 | 202303 | B | 9 | 10 |
2 | 202303 | C | 11 | 12 |
3 | 202304 | A | 11 | 6 |
4 | 202304 | B | 10 | 4 |
5 | 202304 | C | 6 | 7 |
to_records()
Another way to convert pivot tables in Pandas is by:
- extracting data with
to_records()
- create new DataFrame
pd.DataFrame(df_p.to_records())
We get the same result:
date | code | B | R | |
---|---|---|---|---|
0 | 202303 | A | 9 | 5 |
1 | 202303 | B | 9 | 10 |
2 | 202303 | C | 11 | 12 |
3 | 202304 | A | 11 | 6 |
4 | 202304 | B | 10 | 4 |
5 | 202304 | C | 6 | 7 |
Summary
We saw how to convert pivot tables to normal DataFrame in Pandas. This is useful when we need to work with pivot tables as regular DataFrame with MultiIndex.
If you like to unpivot tables you can check the resources below.