how to fix python pandas encoding issue?

Question

I import csv table into JUPYTER NOTEBOOK, and something wrong is happening when I try to iloc a video views column (К-ть переглядів).

I need to format this cell to INT type (using .astype() ), but it tells me that there is an error:

ValueError: invalid literal for int() with base 10: '380\xa0891\xa0555'

Can anyone please tell me what is wrong?

Screenshot:

Answer 1

This is a non breaking space ( chr(160) ). Use str.replace to remove them.

>>> df['A']
0    380 891 555
Name: A, dtype: object

>>> df['A'].dtype.name
'object'

>>> df['A'].astype(int)
ValueError: invalid literal for int() with base 10: '380\xa0891\xa0555'

>>> df['A'].str.replace(chr(160), '').astype(int)
0    380891555
Name: A, dtype: int64

Answer 2

Please see and updated code from another right answer.

# 1. Create a list of encoding;

encoding_list = ['ascii', 'big5', 'big5hkscs', 'cp037', 'cp273', 'cp424', 'cp437', 'cp500', 'cp720', 'cp737', 'cp775', 'cp850', 'cp852', 'cp855', 'cp856', 'cp857', 'cp858', 'cp860', 'cp861', 'cp862', 'cp863', 'cp864', 'cp865', 'cp866', 'cp869', 'cp874', 'cp875', 'cp932', 'cp949', 'cp950', 'cp1006', 'cp1026', 'cp1125', 'cp1140', 'cp1250', 'cp1251', 'cp1252', 'cp1253', 'cp1254', 'cp1255', 'cp1256', 'cp1257', 'cp1258', 'euc_jp', 'euc_jis_2004', 'euc_jisx0213', 'euc_kr', 
                 'gb2312', 'gbk', 'gb18030', 'hz', 'iso2022_jp', 'iso2022_jp_1', 'iso2022_jp_2', 'iso2022_jp_2004', 'iso2022_jp_3', 'iso2022_jp_ext', 'iso2022_kr', 'latin_1', 'iso8859_2', 'iso8859_3', 'iso8859_4', 'iso8859_5', 'iso8859_6', 'iso8859_7', 'iso8859_8', 'iso8859_9', 'iso8859_10', 'iso8859_11', 'iso8859_13', 'iso8859_14', 'iso8859_15', 'iso8859_16', 'johab', 'koi8_r', 'koi8_t', 
                 'koi8_u', 'kz1048', 'mac_cyrillic', 'mac_greek', 'mac_iceland', 'mac_latin2', 'mac_roman', 'mac_turkish', 'ptcp154', 'shift_jis', 'shift_jis_2004', 'shift_jisx0213', 'utf_32', 'utf_32_be', 'utf_32_le', 'utf_16', 'utf_16_be', 'utf_16_le', 'utf_7', 'utf_8', 'utf_8_sig']

# 2. Pass this updated loop to catch only the encoding that works.

for encoding in encoding_list:
    worked = True
    try:
        df = pd.read_csv(path, encoding=encoding, nrows=5, sep=';')
    except:
        worked = False
    if worked:
        if df.iloc[:,0].notna().sum()>0:
            print(f'Encoding that works finally: << {encoding} >>')
        else:
            pass