CODEWITHSUNDEEP
pythonpandasdataframe
Dave
Dave

Reputation: 129

Filtering rows with some NaNs in DFs

I have a dataframes with many rows, and some values are NaNs.
For example -

index  col1     col2    col3
0       1.0     NaN     3.0  
1       NaN     4.0     NaN  
3       1.0     5.0     NaN

I would like to filter the DF and return only the rows with 2+ values.
The number should be configurable.
The resulted DF will be -

index  col1     col2    col3
0       1.0     NaN     3.0  
3       1.0     5.0     NaN

Any idea how can I achieve this result? I've tried creating new column but it doesn't seem the right way.

Thanks!
Code to create the DF:

d = {'col1': [1, None, 1], 'col2': [None, 4, 5], 'col3': [3, None, None]}
df = pd.DataFrame(data=d)
df

Upvotes: 1

Views: 67

Answers (2)

Handri Mauludin Maulana
Handri Mauludin Maulana

Reputation: 75

You can delete the 2nd row by using the drop() method.

ax = df.drop([1])
print(ax)

Upvotes: -1

sophocles
sophocles

Reputation: 13821

You can use dropna() set the threshold to be 2 thresh=2, and perform operation along the rows axis=0:

res = df.dropna(thresh=2,axis=0)

res 
   col1  col2  col3
0  1.00   NaN  3.00
2  1.00  5.00   NaN

https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.dropna.html

Upvotes: 2

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