Pandas Map 0/1 Data Frame Entries To Column Names

I have a data frame in pandas with entries that are either 0 or 1. I would like to reduce this to a single list of strings that are the result from concatentating column names wher

Solution 1:

convert the dtype of the df to a bool, then call apply and use the boolean mask to mask the columns, you need to pass param axis=1 to apply the column mask row-wise:

In [47]:
df.astype(bool).apply(lambda x: ','.join(df.columns[x]), axis=1)

Out[47]:
0    V2,V3
1    V1,V2
2         
dtype: object

Your code my_df.apply(lambda x: colnames[x]) won't work because firstly when calling apply on a df without specifying the axis will call the lambda on each column in turn, secondly the 1/0 will interpret this as an index value rather than a boolean flag.