将pd.Series传递到数据框？

Question

I tried the following code but the new column consists of only NAN values.

df['new'] = pd.Series(np.repeat(1, len(df)))

Can someone explain to me what the problem is here?

Answer 1

It is possible that the index of the DataFrame df does not match with the newly created Series'. For example,

import pandas as pd
import numpy as np
df = pd.DataFrame({'a': [11, 22, 33, 44, 55]}, index=['r1','r2','r3','r4','r5'])
df['new'] = pd.Series(np.repeat(1, len(df)))
print df

and the output will be:

     a  new
r1  11  NaN
r2  22  NaN
r3  33  NaN
r4  44  NaN
r5  55  NaN

since the index of pd.Series(np.repeat(1, len(df))) is Int64Index([0, 1, 2, 3, 4], dtype='int64') .

To prevent that, specify the index argument when creating the Series:

df['new'] = pd.Series(np.repeat(1, len(df)), index=df.index)

Alternatively, you can just pass a numpy array if the index is to be ignored:

df['new'] = np.repeat(1, len(df))

without needing to create a Series (in fact, df['new'] = 1 will do for this case). Using a Series is helpful when you need to align the new column with the existing DataFrame using the index.