I know I can rename single pandas.DataFrame columns with:
drugInfo.rename(columns = {'col_1': 'col_1_new_name'}, inplace = True) But I'd like to rename a column based on its index (without knowing its name) - although I know dictionaries don't have it). I would like to rename column number 1 like this:
drugInfo.rename(columns = {1: 'col_1_new_name'}, inplace = True) But in the DataFrame.columns dict there is no '1' entry, so no renaming is done. How could I achieve this?
Should work:
drugInfo.rename(columns = {list(drugInfo)[1]: 'col_1_new_name'}, inplace = True) Example:
In [18]: df = pd.DataFrame({'a':randn(5), 'b':randn(5), 'c':randn(5)}) df Out[18]: a b c 0 -1.429509 -0.652116 0.515545 1 0.563148 -0.536554 -1.316155 2 1.310768 -3.041681 -0.704776 3 -1.403204 1.083727 -0.117787 4 -0.040952 0.108155 -0.092292 In [19]: df.rename(columns={list(df)[1]:'col1_new_name'}, inplace=True) df Out[19]: a col1_new_name c 0 -1.429509 -0.652116 0.515545 1 0.563148 -0.536554 -1.316155 2 1.310768 -3.041681 -0.704776 3 -1.403204 1.083727 -0.117787 4 -0.040952 0.108155 -0.092292 It is probably more readable to index into the dataframe columns attribute:
df.rename(columns={df.columns[1]:'col1_new_name'}, inplace=True) So for you:
drugInfo.rename(columns = {drugInfo.columns[1]: 'col_1_new_name'}, inplace = True) To change a column name by index, one could alter the underlying array of df.columns by index. So
df.columns.array[1] = 'col_1_new_name' # or df.columns.values[1] = 'col_1_new_name' # or df.columns.to_numpy()[1] = 'col_1_new_name' They all perform the following transformation (without referencing B, it is changed):
However, if a new dataframe copy needs to be returned, rename method is the way to go (as suggested by EdChum):
df1 = df.rename(columns={list(df)[1]: 'col_1_new_name'}) If df has many columns, instead of list(df), it might be worth it to call islice() from the standard itertools library to efficiently select a column label (e.g. the second column name):
from itertools import islice df1 = df.rename(columns={next(islice(df, 1, 2)): 'col_1_new_name'})