filling NAN and converting to int pandas

Question

I have a dataframe of integers. Preview (starts from 3 due to first 3 rows removal):

The original data in the 'pixel1' column is int, but the NAN there forced it to float.

I tried to fix it with:

X_train.fillna(method='ffill', inplace=True)
X_train = X_train.astype(int)
print(X_train.head())

that results in:

• can I get the datatype of the value the fillna is using?
• is there a better way to do so? (better = to skip the astype step, as the data is int originally - I planted the NAN in the file and that caused the int to float unwanted data conversion...)

Answer 1

I suggest use ffill with bfill for back filling if possible some NaNs in first row:

X_train = X_train.ffill().bfill().astype(int)

If not:

X_train = X_train.ffill().astype(int)