Python - use the print in the next code

Question

This code generates the columns with missing's (it is ok)

for a in data.columns:
    if data[a].isnull().any() == True:
        print (a)

and now I want to use the columns of the previous code to apply to the following code

data[a].isnull().sum()

but the 'a' does not save the column names with missing's, is just the name of the last column. I need to use something like b=print (a) and doing the append do a list but I can´t find the right code.

Honestly this question isn't that clear, please consider editing it. If you need to save the items that trigger the conditional create something like a list then append to it. — shuttle87
– shuttle87, Commented Mar 27, 2018 at 12:33
I dont excatly understand what you want to do.. Get the number of empty collumns in data? — Rohi
– Rohi, Commented Mar 27, 2018 at 12:33
This is an XY problem. Don't ask about appending values to a list when in reality you want to do something else. If I understand the problem correctly, you want to count the NaN values in each column? — Aran-Fey
– Aran-Fey, Commented Mar 27, 2018 at 12:35
yes I want to get the number of empty columns in data but i just want to use the columns that are print in the first code, I don't want to see the others columns. I have this question on this code but I also want to understand how can I use the printing variables in other's codes because I need to use in more codes. — rk jp
– rk jp, Commented Mar 27, 2018 at 12:39
Thanks for clarifying, but I suggest you clean up your question and provide a minimal reproducible example. Show an example of a dataframe with some NaN values and the result you want to get. — Aran-Fey
– Aran-Fey, Commented Mar 27, 2018 at 12:42

Rakesh · Accepted Answer · 2018-03-27 12:47:02Z

1

Looks like you are looking for.

res = [data[a].isnull().sum() for a in data.columns]
print(res)

answered Mar 27, 2018 at 12:47

Rakesh

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Bryce Ramgovind · Accepted Answer · 2018-03-27 13:08:42Z

1

This will provide a list of columns has nulls/NaNs

null_index = df.isnull().any()
a= null_index[null_index==True].index.tolist()

a will have a list of all the column names that has nulls in the column.

edited Mar 27, 2018 at 13:08

answered Mar 27, 2018 at 13:00

Bryce Ramgovind

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