import pandas as pd
import numpy as np

# Assuming 'a' is a pandas Series
a = pd.Series(['bear', 'fox', 'wolf', 'mouse'])

# Splitting the characters and stacking them as columns
split_chars = a.str.split('', expand=True).drop(0, axis=1)

# Creating 'ao' column by joining the characters
ao = a.str.cat(sep='')

# Printing the results
print(split_chars)
print(ao)

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你可以用正则表达式（和lookarounds）split并展开它：

out = df['a'].str.split(r'(?<=.)(?=.)', expand=True)

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split的regex demo。
或者，使用extractall获取每个字符，然后使用unstack进行整形：

out = (df['a'].str.extractall('(.)')[0]
       .unstack('match')
       .rename_axis(columns=None)
      )

型
输出量：

0  1  2    3    4
0  b  e  a    r  NaN
1  f  o  x  NaN  NaN
2  w  o  l    f  NaN
3  m  o  u    s    e

型

另一个可能的解决方案：

pd.concat(list(df['a'].map(lambda x: pd.DataFrame(list(x)))),
          axis=1).T.reset_index(drop=True)

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输出量：

0  1  2    3    4
0  b  e  a    r  NaN
1  f  o  x  NaN  NaN
2  w  o  l    f  NaN
3  m  o  u    s    e

型