Create Dataframe Columns Automatically with Different Names-CodePudding

How can I create dataframe columns automatically with different names

I have this code

df=pd.DataFrame(columns=['A']*5)
df.loc[len(df)]=[1,2,3,4,5]

Which gives the result

   A  A  A  A  A
0  1  2  3  4  5

And I want the column names to be

   A1  A2  A3  A4  A5
0  1   2   3   4   5

CodePudding user response：

If possible pass to DataFrame correct columns names:

df=pd.DataFrame(columns=[f'A{i}' for i in range(1, 6)])
df.loc[len(df)]=[1,2,3,4,5]
print (df)
  A1 A2 A3 A4 A5
0  1  2  3  4  5

If need change values later with enumerate all columns names use:

df=pd.DataFrame(columns=['A']*5)

s = df.columns.to_series()
df.columns  = s.groupby(s).cumcount().add(1).astype(str)
df.loc[len(df)]=[1,2,3,4,5]

print (df)
  A1 A2 A3 A4 A5
0  1  2  3  4  5

df=pd.DataFrame(columns=['A']*2   ['B'] * 2   ['C'])

s = df.columns.to_series()

df.columns  = s.groupby(s).cumcount().add(1).astype(str)

df.loc[len(df)]=[1,2,3,4,5]

print (df)
  A1 A2 B1 B2 C1
0  1  2  3  4  5

CodePudding user response：

One option is with enumerate, if you are doing this after creating the DataFrame (doing this when creating the DataFrame, as suggested by @jezrael, IMO is a better option):

df.columns = [f"{col}{num 1}" for num, col in enumerate(df.columns)]
df

   A1  A2  A3  A4  A5
0   1   2   3   4   5

CodePudding user response：

To handle an arbitrary input list use enumerate:

df=pd.DataFrame(columns=[f'{a}{b}' for b,a in enumerate(['A']*5, start=1)])
df.loc[len(df)]=[1,2,3,4,5]

To handle any type of object without creating a copy, use itertools.repeat:

from itertools import repeat
df=pd.DataFrame(columns=[f'{a}{b 1}' for a,b in zip(repeat('A'), range(5))])
df.loc[len(df)]=[1,2,3,4,5]

output:

   A1  A2  A3  A4  A5
0   1   2   3   4   5