Delete row from a column that is unnamed or blank using pandas-CodePudding

I have a dataframe, df, where I would like to delete a row from a column that is unnamed or blank using pandas. I would like to delete the row that contains 'id'

Data

        a   b   c
date    21  22  23
id          
aa      2   3   4
bb      1   2   3
cc      5   5   5

Desired

        a   b   c
date    21  22  23
aa      2   3   4
bb      1   2   3
cc      5   5   5

Doing

df[df[""].str.contains("id")==False]

df.drop(1)

However, the action is not executed and I do not get the desired result. I am actively researching this. Any suggestions are appreciated

CodePudding user response：

Use dropna:

>>> df.dropna(how='all', axis=0)
         a     b     c
date  21.0  22.0  23.0
aa     2.0   3.0   4.0
bb     1.0   2.0   3.0
cc     5.0   5.0   5.0

Update

If the first column is not an index but a real column with an empty name, maybe you should use this version:

>>> df[df.loc[:, df.columns.str.len().astype(bool)].notna().any(axis=1)]

            a     b     c
0  date  21.0  22.0  23.0
2    aa   2.0   3.0   4.0
3    bb   1.0   2.0   3.0
4    cc   5.0   5.0   5.0

Or more simple, if your unnamed column is the first:

>>> df[df.iloc[:, 1:].notna().any(axis=1)]
            a     b     c
0  date  21.0  22.0  23.0
2    aa   2.0   3.0   4.0
3    bb   1.0   2.0   3.0
4    cc   5.0   5.0   5.0

CodePudding user response：

Regardless, you have a row with space. Way out is to query df for such rows and filter them out. Space, indicates a dtype object. I would

df.where((df!=' ')).dropna()



        a     b     c
date  21.0  22.0  23.0
aa     2.0   3.0   4.0
bb     1.0   2.0   3.0
cc     5.0   5.0   5.0

CodePudding user response：

Run this command, it will drop all column which contain any null values

data = data.dropna()