Drop the first (or any nth) column whose name contains a specific string from pandas DataFrame

Question

Let's say I have a pandas DataFrame as follows:

df = pd.DataFrame([[1,2,3,4,5],[6,7,8,9,10]],columns=['a1693','b1124','b113','a2609', 'a1'])

I want to drop, for example, b1124 . How do I do it?

I can get the column as a pd.Series by using the following code.

df.loc[:,df.columns.str.contains('b')].iloc[:,0]

But I don't know how to drop it from df .

Also, if I want to do the same for multiple columns, ie drop a1693 and b1124 , how do I do that as well?

Answer 1

add filter

df = df.drop(df.columns[df.columns.str.contains('b')][0],1)
   a1693  b113  a2609  a1
0      1     3      4   5
1      6     8      9  10

Answer 2

In [28]: N = 0

In [29]: df.drop(df.columns[np.where(df.columns.str.contains("b")==True)[0][N]], axis=1)
Out[29]:
   a1693  b113  a2609  a1
0      1     3      4   5
1      6     8      9  10

In [30]: N = 1

In [31]: df.drop(df.columns[np.where(df.columns.str.contains("b")==True)[0][N]], axis=1)
Out[31]:
   a1693  b1124  a2609  a1
0      1      2      4   5
1      6      7      9  10