I have a list of Data Frames in which some Data Frames have NaN values. So far I can identify NaN values for a single Data Frame using this link.
How can I find the index of the list where a Data Frame has NaN values.
Sample list of dffs,
[
var1 var1
14.171250 13.593813
13.578317 13.595329
10.301850 13.580139
9.930217 NaN
6.192517 13.561943
NaN 13.565149
6.197983 13.572509,
var1 var2
2.456183 5.907528
5.052017 5.955731
5.960000 5.972480
8.039317 5.984608
7.559217 5.985348
6.933633 5.979438,
var1 var1
14.171250 23.593813
23.578317 23.595329
56.301850 23.580139
90.930217 22.365676
89.192517 33.561943
86.23654 53.565149
NaN 13.572509,
...]
I need to get the results in a list indexes 0 and 2 that have NaN values.
So far I tried this,
df_with_nan = []
for df in dffs:
df_with_nan.append(df.columns[df.isnull().any()])
Per above for loop I get column names, var1 and var2. However, I need the indexes of those Data Frames when i loop through it. Any help or suggestion would be great.