Pandas.DataFrame.str.replace函数将浮点数替换为NaN
问题描述：
我有一个Pandas DataFrame，假设:
df = pd.DataFrame({'Column name':['0,5',600,700]})
I have a Pandas DataFrame, suppose:
df = pd.DataFrame({'Column name':['0,5',600,700]})
我需要删除,.代码是:
df_mod = df.stack().str.replace(',','').unstack()
I need to remove ,. The code is:
df_mod = df.stack().str.replace(',','').unstack()
结果是:[05, NaN, NaN]
您是否知道我的表达式为何用NaN替换数字以及如何避免呢?非常感谢！
Do you have any ideas why my expression replaces numbers with NaN and how to avoid it? Thanks a lot!
答
那些数字被视为没有str.replace方法的数字值，您可以将列转换为字符串，删除逗号，然后转换数据类型返回:
Those numbers are treated as numeric values, which don't have str.replace methods, you can convert the column to string, remove the comma, and then convert the data type back:
df['Column name'].astype(str).str.replace(",", "").astype(int)
#0 5
#1 600
#2 700
#Name: Column name, dtype: int64