How do I remove float and NaN

Question:

I’m trying to convert a list with over 20 rows and convert into a data frame but I’m running into an issue. When I convert my list, it returns a float and nan in some of the numbers in my data frame. Is there a way to fix this issue?
For example, below

 lst = [[2,25,26],[5],[10,19,19],[20,18,18]]


I tried this code df1 = pd.DataFrame(lst) but it doesn't work. 
 
   0     1     2
0  2  25.0  26.0
1  5   NaN   NaN
2  10  19.0  19.0
3  20  18.0  18.0

I would like to remove Nan, decimal and zero but still keep the values and the same index.

       0    1    2
   0   2   25   26
   1   5          
   2  10   19   19
   3  20   18   18
Asked By: Chris

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Answers:

NaN values are missing values, so indicates that there is nothing in that position

On the other hand, the value 5 still has the same position [1][0]

Answered By: 4 3 2

NaN is a missing value in a data frame. It’s the representation that nothing is there – another way of thinking about it would be Null. You can however, change the data type to int even though there is NaN present. You can do this with the following:

df1 = df1.astype("Int64")

Which gives the following:

    0     1     2
0   2    25    26
1   5  <NA>  <NA>
2  10    19    19
3  20    18    18
Answered By: Marcelo Paco