Pandas Invalid Literal For Long() With Base 10 Error

I am trying to do: df['Num_Detections'] = df['Num_Detections'].astype(int) And i get following error: ValueError: invalid literal for long() with base 10: '12.0' My data looks

Solution 1:

There is some value, which cannot be converted to int.

You can use to_numeric and get NaN where is problematic value:

df['Num_Detections'] = pd.to_numeric(df['Num_Detections'], errors='coerce')

If need check rows with problematic values, use boolean indexing with mask with isnull:

print (df[ pd.to_numeric(df['Num_Detections'], errors='coerce').isnull()])

Sample:

df = pd.DataFrame({'Num_Detections':[1,2,'a1']})

print (df)
  Num_Detections
0              1
1              2
2             a1

print (df[ pd.to_numeric(df['Num_Detections'], errors='coerce').isnull()])
  Num_Detections
2             a1

df['Num_Detections'] = pd.to_numeric(df['Num_Detections'], errors='coerce')
print (df)
   Num_Detections
0             1.0
1             2.0
2             NaN