CODEWITHSUNDEEP
pythonpandas
Jiaye
Jiaye

Reputation: 41

Storing 3-dimensional data in pandas DataFrame

I am new to Python and I'm trying to understand how to manipulate data with pandas DataFrames. I searched for similar questions but I don't see any satisfying my exact need. Please point me to the correct post if this is a duplicate.

So I have multiple DataFrames with the exact same shape, columns and index. How do I combine them with labels so I can easily access the data with any column/index/label?

E.g. after the setup below, how do I put df1 and df2 into one DataFrame and label them with the names 'df1' and 'df2', so I can access data in a way like df['A']['df1']['b'], and get number of rows of df?

>>> import numpy as np
>>> import pandas as pd
>>> df1 = pd.DataFrame([[1, 2], [3, 4]], columns=['A', 'B'], index=['a', 'b'])
>>> df2 = pd.DataFrame([[5, 6], [7, 8]], columns=['A', 'B'], index=['a', 'b'])
>>> df1
   A  B
a  1  2
b  3  4
>>> df2
   A  B
a  5  6
b  7  8

Upvotes: 2

Views: 14011

Answers (2)

Christabella Irwanto
Christabella Irwanto

Reputation: 1201

Using xarray is recommended, as other answers to similar questions have suggested. Since pandas Panels were deprecated in favour of xarray.

Upvotes: 0

jezrael
jezrael

Reputation: 862801

I think MultiIndex DataFrame is answer created by concat:

df = pd.concat([df1, df2], keys=('df1','df2'))
print (df)
       A  B
df1 a  1  2
    b  3  4
df2 a  5  6
    b  7  8

Then for basic select is possible use xs:

print (df.xs('df1'))
   A  B
a  1  2
b  3  4

And for select index and columns together use slicers:

idx = pd.IndexSlice
print (df.loc[idx['df1', 'b'], 'A'])
3

Another possible solution is use panels.

But in newer versions of pandas is deprecated.

Upvotes: 10

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