converting a column of object values to float or integers. ValueError: invalid literal for int() with base 10: '1,026,765'

Question

  dfproduction = pd.read_csv('https://raw.githubusercontent.com/chessybo/Oil-Spill-map/master/Oil%20Spill%20Data%20-%20Crude%20Oil%2C%20Gas%20Well%20Liquids%20or%20Associated%20Products%20(H-8)/production%20data/Crude%20Oil%20Production%20and%20Well%20Counts%20(since%201935).csv', encoding='utf-8')

我想将此数据转换为数字（即列，'Crude Oil Production (Mbbl)'），例如 float 或 int。

当前数据类型是对象

    print(dfproduction.dtypes)
MasterYear                                  int64
Crude Oil Production (Mbbl)                object
Daily Avg. Production (Mbbl/day)           object
Number of Producing Wells                  object
Percent Change in Production               object
Avg. Per Well Production (bbl/day)        float64
Crude Oil Reserves as of Jan. 1 (Mbbl)     object
info                                       object
dtype: object

然而，任何这样做的尝试都会导致某种形式的错误。

dfproduction['Crude Oil Production (Mbbl)'].astype('int')
ValueError: invalid literal for int() with base 10: '1,026,765'

dfproduction['Crude Oil Production (Mbbl)'].astype('float')
ValueError: could not convert string to float: '375,617'

更新：

问题是数字中的逗号，我删除了逗号并重新上传了数据。直到现在我才收到以下错误..

UnicodeDecodeError: 'utf-8' codec can't decode byte 0xa0 in position 83: invalid start byte

Answer 1

使用 str.replace() 删除逗号。

dfproduction['Crude Oil Production (Mbbl)'].str.replace(r',', '').astype('int')

converting a column of object values to float or integers. ValueError: invalid literal for int() with base 10: '1,026,765'

converting a column of object values to float or integers. ValueError: invalid literal for int() with base 10: '1,026,765'

python

typeerror

python-3.x

pandas

valueerror