df1 = pd.DataFrame(np.arange(15).reshape(5,3))
df1.iloc[:4,1] = np.nan
df1.iloc[:2,2] = np.nan
df1.dropna(thresh=1 ,axis=1)
It seems that no nan value has been deleted.
0 1 2
0 0 NaN NaN
1 3 NaN NaN
2 6 NaN 8.0
3 9 NaN 11.0
4 12 13.0 14.0
if i run
df1.dropna(thresh=2,axis=1)
why it gives the following?
0 2
0 0 NaN
1 3 NaN
2 6 8.0
3 9 11.0
4 12 14.0
i just dont understand what thresh is doing here. If a column has more than one nan value, should the column be deleted?
thresh=N requires that a column has at least N non-NaNs to survive. In the first example, both columns have at least one non-NaN, so both survive. In the second example, only the last column has at least two non-NaNs, so it survives, but the previous column is dropped.
Try setting thresh to 4 to get a better sense of what's happening.