I have a dataframe in which the 1st column in some of the rows are empty, and I want to drop such rows. I saw this as one way to drop row:

df = df.dropna(axis=0, subset=['1st_row']) 

I don't know the column names and I want to drop by column index (the 1st column). Is that possible?

CodePudding user response：

you could select columns (or rows) by position using iloc

for instance, the following would drop all rows where the first column is null

df = pd.DataFrame({
   'a': [pd.NA, 1, 2, 3, pd.NA, 4, 5],
   'b': list('abcdefg')
})
df2 = df[df.iloc[:,0].notnull()]

df2 outputs:

   a  b
1  1  b
2  2  c
3  3  d
5  4  f
6  5  g