How to shift several rows in a pandas DataFrame?

Question

I have the following pandas Dataframe:

import pandas as pd
data = {'one' : pd.Series([1.], index=['a']), 'two' : pd.Series([1., 2.], index=['a', 'b']), 'three' : pd.Series([1., 2., 3., 4.], index=['a', 'b', 'c', 'd'])}
df = pd.DataFrame(data)
df = df[["one", "two", "three"]]


   one  two  three
a  1.0  1.0    1.0
b  NaN  2.0    2.0
c  NaN  NaN    3.0
d  NaN  NaN    4.0

I know how to shift elements by column upwards/downwards, e.g.

df.two = df.two.shift(-1)

   one  two  three
a  1.0  2.0    1.0
b  NaN  NaN    2.0
c  NaN  NaN    3.0
d  NaN  NaN    4.0

However, I would like to shift all elements in row a over two columns and all elements in row b over one column. The final data frame would look like this:

   one  two  three
a  NaN  NaN    1.0
b  NaN  NaN    2.0
c  NaN  NaN    3.0
d  NaN  NaN    4.0

How does one do this in pandas?

Answer 1

IMHO, this is a more pythonic way:

df.loc['a'] = df.loc['a'].shift(periods=2,axis=0)

Note in this case .loc returns a Series, so axis=0 is optional.

Answer 2

You can transpose the initial DF so that you have a way to access the row labels as column names inorder to perform the shift operation.

Shift the contents of the respective columns downward by those amounts and re-transpose it back to get the desired result.

df_t = df.T
df_t.assign(a=df_t['a'].shift(2), b=df_t['b'].shift(1)).T