How to move content of a column to a column next to it - python-3.x

Question

The dataframe looks like this:
import pandas as pd
df = pd.DataFrame ({
'Name':['Brian','John','Adam'],
'HomeAddr':[12,32,44],
'Age':['M','M','F'],
'Genre': ['NaN','NaN','NaN']
})
The current output is:
Name HomeAddr Age Genre
0 Brian 12 M NaN
1 John 32 M NaN
2 Adam 44 F NaN
I would like to shift somehow content of HomeAddr and Age columns to columns+1. Below is a sample of the expected output.
Name HomeAddr Age Genre
0 Brian NaN 12 M
1 John NaN 32 M
2 Adam NaN 44 F
I tried with .shift() but it doesn't work.
import pandas as pd
df = pd.DataFrame ({
'Name':['Brian','John','Adam'],
'HomeAddr':[12,32,44],
'Age':['M','M','F'],
'Genre': ['NaN','NaN','NaN']
})
df['HomeAddr'] = df['HomeAddr'].shift(-1)
print(df)
Name HomeAddr Age Genre
0 Brian 32.0 M NaN
1 John 44.0 M NaN
2 Adam NaN F NaN
Any ideas guys? Thank you!

Answer 1

Use DataFrame.shift, but is necessary convert columns to strings for avoid missing values, then convert numeric columns back:
df.loc[:, 'HomeAddr':] = df.loc[:, 'HomeAddr':].astype(str).shift(1, axis=1)
df['Age'] = pd.to_numeric(df['Age'])
print (df)
Name HomeAddr Age Genre
0 Brian NaN 12 M
1 John NaN 32 M
2 Adam NaN 44 F
Another out of box solution:
df = df.drop('Genre', axis=1).rename(columns={'HomeAddr':'Age', 'Age':'Genre'})
df.insert(1, 'HomeAddr', np.nan)
print (df)
Name HomeAddr Age Genre
0 Brian NaN 12 M
1 John NaN 32 M
2 Adam NaN 44 F