Pandas Dataframe add header without replacing current header

Question

How to add a title to DF without replacing the current one? In other words, I just want to move the current header down and just add it to the dataframe as another record.

* secondary question: how to add tables (example dataframe) to stackoverflow question?

I have this (note heading and how it is simply added as a string:

0.213231 0.314544 0 -0.952928 -0.624646 1 -1.020950 -0.883333 

I need it (all other entries are pushed down and a new entry is added) (also: I could not read csv correctly, because I use s3_text_adapter to import, and I could not figure out how to have an argument that ignores a header similar to pandas read_csv):

  AB 0 0.213231 0.314544 1 -1.020950 -0.883333 

Answer 1

Another option is to add it as an additional column index level to make it MultiIndex:

 In [11]: df = pd.DataFrame(randn(2, 2), columns=['A', 'B']) In [12]: df Out[12]: AB 0 -0.952928 -0.624646 1 -1.020950 -0.883333 In [13]: df.columns = pd.MultiIndex.from_tuples(zip(['AA', 'BB'], df.columns)) In [14]: df Out[14]: AA BB AB 0 -0.952928 -0.624646 1 -1.020950 -0.883333 

This allows you to save the correct data types for the DataFrame, so you can perform fast and correct calculations in your DataFrame and allow you to access both old and new column names.

.

For completeness, here is DSM (remote response), making the columns a row, which, as already mentioned, is usually not a good idea:

 In [21]: df_bad_idea = df.T.reset_index().T In [22]: df_bad_idea Out[22]: 0 1 index AB 0 -0.952928 -0.624646 1 -1.02095 -0.883333 

Note that dtype can change (if it's the column names and not the correct values), as in this case ... so be careful if you are actually planning to do any work on this, as it probably will be slower and may not even work

 In [23]: df.sum() Out[23]: A -1.973878 B -1.507979 dtype: float64 In [24]: df_bad_idea.sum() # doh! Out[24]: Series([], dtype: float64) 

If the column names is a line that was erroneous as a header line, then you should fix this when reading in the data (e.g. read_csv use header=None ).

Answer 2

The key is to specify header = None and use the column to add the header:

 data = pd.read_csv('file.csv', skiprows=2, header=None ) # skip blank rows if applicable df = pd.DataFrame(data) df = df.iloc[ : , [0,1]] # columns 1 and 2 df.columns = ['A','B'] # title