Pandas copy column names from one dataframe to another

Just like you have used columns from the dataframe with column names, you can use values from the dataframe without column names:

new_df_with_col_names = pd.DataFrame(data=no_col_names_df.values, columns=col_names_df.columns)

---

In [4]: new_df_with_col_names = pd.DataFrame(data=no_col_names_df, columns=col_names_df.columns)

In [5]: new_df_with_col_names
Out[5]:
   col1  col2  col3
0   NaN   NaN   NaN
1   NaN   NaN   NaN
2   NaN   NaN   NaN

In [6]: new_df_with_col_names = pd.DataFrame(data=no_col_names_df.values, columns=col_names_df.columns)

In [7]: new_df_with_col_names
Out[7]:
   col1  col2  col3
0     1     2     3
1     4     5     6
2     7     8     9

This:

pd.DataFrame(data=no_col_names_df, columns=col_names_df.columns)

gives you all 'NaN' dataframe because you pass a dataframe to construct a new dataframe and assign new columns to it. Pandas essentially constructs identical dataframe and does reindex along axis 1on it. In other words, that command is equivalent to doing:

no_col_names_df.reindex(col_names_df.columns, axis=1)

You need either change directly no_col_names_df.columns or passing no_col_names_df.values

The simplest way is to directly assign the columns of col_names_df to the ones of no_col_names_df:

no_col_names_df.columns = col_names_df.columns

     col1  col2  col3
0     1     2     3
1     4     5     6
2     7     8     9