I wanted to replace the ‘na’ value in the output with 0.0. Those are not NaN values. It had ‘na’ value in the csv file.
I tried every method I thought I could to replace na with 0.0 but to no avail.
Here is the output:
Brunei Darussalam Indonesia Malaysia Philippines Thailand Viet Nam Myanmar Japan ... Austria Scandinavia CIS & Eastern Europe USA Canada Australia New Zealand Africa
...
1978 Jan na na na na na na na 18,652 ... na 1,881 433 8,362 1,328 28,421 3,612
587
1978 Feb na na na na na na na 20,394 ... na 2,112 514 8,251 1,434 13,982 2,521
354
1978 Mar na na na na na na na 20,136 ... na 2,183 472 9,901 1,662 16,536 2,727
405
1978 Apr na na na na na na na 13,508 ... na 1,590 405 11,782 1,586 16,499 3,197
736
1978 May na na na na na na na 14,472 ... na 1,245 431 13,448 2,025 20,690 5,130
514
What the output is supposed to look like:
Brunei Darussalam Indonesia Malaysia Philippines Thailand Vietnam Myanmar Japan ... Austria Scand0.0via CIS & Eastern Europe USA Canada Australia New Zealand Africa
...
1978 Jan 0.0 0.0 0.0 0.0 0.0 0.0 0.0 18,652 ... 0.0 1,881 433 8,362 1,328 28,421 3,612
587
1978 Feb 0.0 0.0 0.0 0.0 0.0 0.0 0.0 20,394 ... 0.0 2,112 514 8,251 1,434 13,982 2,521
354
1978 Mar 0.0 0.0 0.0 0.0 0.0 0.0 0.0 20,136 ... 0.0 2,183 472 9,901 1,662 16,536 2,727
405
1978 Apr 0.0 0.0 0.0 0.0 0.0 0.0 0.0 13,508 ... 0.0 1,590 405 11,782 1,586 16,499 3,197
736
1978 May 0.0 0.0 0.0 0.0 0.0 0.0 0.0 14,472 ... 0.0 1,245 431 13,448 2,025 20,690 5,130
514
I tried converting with fillna, but it did not work. I even tried numpy to convert it to zeroes, but it did not work. Here is my code below
import pandas as pd
import numpy as np
df = pd.read_csv('Int_Monthly_Visitor.csv', header=0, index_col=0, na_values=0.0)
print(df.head(5).replace(np.nan, 0.0))
So far I was not able to make it work. I can give the CSV file if needed.
>Solution :
Since you are reading CSV file, you can directly pass na to na_values parameter of read_csv function (currently you are passing 0.0), then you can call fillna(0) either for entire dataframe, or for the columns of your choice:
pd.read_csv('Int_Monthly_Visitor.csv', header=0, index_col=0, na_values=['na']).fillna(0)
Brunei Darussalam Indonesia Malaysia ... Australia New Zealand Africa
0 1978 Jan 0.0 0.0 ... 1,328 28,421 3,612
1 1978 Feb 0.0 0.0 ... 1,434 13,982 2,521
2 1978 Mar 0.0 0.0 ... 1,662 16,536 2,727
3 1978 Apr 0.0 0.0 ... 1,586 16,499 3,197
4 1978 May 0.0 0.0 ... 2,025 20,690 5,130
[5 rows x 16 columns]