The answer is
You can add parameter columns or use dict with key which is converted to column name:
np.random.seed(123)
e = np.random.normal(size=10)
dataframe=pd.DataFrame(e, columns=['a'])
print (dataframe)
a
0 -1.085631
1 0.997345
2 0.282978
3 -1.506295
4 -0.578600
5 1.651437
6 -2.426679
7 -0.428913
8 1.265936
9 -0.866740
e_dataframe=pd.DataFrame({'a':e})
print (e_dataframe)
a
0 -1.085631
1 0.997345
2 0.282978
3 -1.506295
4 -0.578600
5 1.651437
6 -2.426679
7 -0.428913
8 1.265936
9 -0.866740
In general you can use pandas rename function here. Given your dataframe you could change to a new name like this. If you had more columns you could also rename those in the dictionary. The 0 is the current name of your column
import pandas as pd
import numpy as np
e = np.random.normal(size=100)
e_dataframe = pd.DataFrame(e)
e_dataframe.rename(index=str, columns={0:'new_column_name'})
Source: Stackoverflow.com