pandas dropna() 仅当在第一行 NaN 值中时

Question

I have a dataframe like the following

df = [[1,'NaN',3],[4,5,'Nan'],[7,8,9]]
df = pd.DataFrame(df)

and I would like to remove all columns that have in their first row a NaN value.

So the output should be:

df = [[1,3],[4,'Nan'],[7,9]]
df = pd.DataFrame(df)

So in this case, only the second column is removed since the first element was a NaN value. Hence, dropna() is based on a condition.. any idea how to handle this? Thx!

Answer 1

If values are np.nan and not string NaN ( else replace them ), you can do:

Input:

df = [[1,np.nan,3],[4,5,np.nan],[7,8,9]]
df = pd.DataFrame(df)

---

Solution:

df.loc[:,df.iloc[0].notna()] #assign back to your desired variable

   0    2
0  1  3.0
1  4  NaN
2  7  9.0