如何在 Pandas 中使用 base 10 错误修复 int() 的无效文字
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How do I fix invalid literal for int() with base 10 error in pandas
提问by Caribgirl
This is the error that is showing up whenever i try to convert the dataframe to int.
这是每当我尝试将数据帧转换为 int 时出现的错误。
("invalid literal for int() with base 10: '260,327,021'", 'occurred at index Population1'
（“以 10 为基数的 int() 的无效文字：'260,327,021'”，'发生在索引 Population1'
Everything in the df is a number. I assume the error is due to the extra quote at the end but how do i fix it?
df 中的所有内容都是数字。我认为错误是由于最后的额外报价引起的，但我该如何解决？
回答by piRSquared
I run this
我运行这个
int('260,327,021')
and get this
得到这个
--------------------------------------------------------------------------- ValueError Traceback (most recent call last) <ipython-input-448-a3ba7c4bd4fe> in <module>() ----> 1 int('260,327,021') ValueError: invalid literal for int() with base 10: '260,327,021'
--------------------------------------------------------------------------- ValueError Traceback (most recent call last) <ipython-input-448-a3ba7c4bd4fe> in <module>() ----> 1 int('260,327,021') ValueError: invalid literal for int() with base 10: '260,327,021'
I assure you that not everything in your dataframe is a number. It may look like a number, but it is a string with commas in it.
我向您保证，并非数据框中的所有内容都是数字。它可能看起来像一个数字，但它是一个包含逗号的字符串。
You'll want to replace your commas and then turn to an int
你会想要替换你的逗号，然后转向 int
pd.Series(['260,327,021']).str.replace(',', '').astype(int)
0 260327021
dtype: int64
回答by kristian
Others might encounter the following issue, when the string is a float:
当字符串是浮点数时，其他人可能会遇到以下问题：
>>> int("34.54545")
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ValueError: invalid literal for int() with base 10: '34.54545'
The workaround for this is to convert to a float first and then to an int:
解决方法是先转换为浮点数，然后再转换为整数：
>>> int(float("34.54545"))
34
Or pandas specific:
或Pandas特定：
df.astype(float).astype(int)
回答by Abhishek Sinha
I solved the error using pandas.to_numeric
我使用pandas.to_numeric解决了错误
In your case,
在你的情况下，
data.Population1 = pd.to_numeric(data.Population1, errors="coerce")
'data' is the parent Object.
“数据”是父对象。
After that, you can convert float to int as well
之后，您也可以将 float 转换为 int
data.Population1.astype(int)
