Drop dataframe columns based on if condition in pandas

Question

I have the following dataframe

 2001-01-01   2001-01-02            2001-01-03 
   1               0                   8 

I want to drop every column, which is smaller than 2001-01-02, ie my df should look like this:

  2001-01-02            2001-01-03
          0                   8 

Does anybody know how to do it?

Answer 1

Use 'inverse' condition < to >= , because need only values equal or higher:

df = pd.DataFrame([[1,0,8]], columns = pd.date_range('2001-01-01', periods=3))
print (df)
   2001-01-01  2001-01-02  2001-01-03
0           1           0           8

print (df.columns >= '2001-01-02')
[False  True  True]


df1 = df.loc[:, df.columns >= '2001-01-02']
print (df1)
   2001-01-02  2001-01-03
0           0           8

cols = df.columns[df.columns >= '2001-01-02']
df1 = df[cols]
print (df1)
   2001-01-02  2001-01-03
0           0           8

Another solution is add ~ for inverse boolean array :

df1 = df.loc[:, ~(df.columns < '2001-01-02')]
print (df1)
   2001-01-02  2001-01-03
0           0           8

Answer 2

You can use label slices with loc

df.loc[:, :'2001-01-02']

   2001-01-01  2001-01-02
0           1           0

And

df.loc[:, '2001-01-02':]

   2001-01-02  2001-01-03
0           0           8