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如何将'number'拆分为pandas DataFrame中的单独列

[英]how to split 'number' to separate columns in pandas DataFrame

I have a dataframe; 我有一个数据帧;

df=pd.DataFrame({'col1':[100000,100001,100002,100003,100004]})

     col1    
0   100000    
1   100001
2   100002
3   100003
4   100004

I wish I could get the result below; 我希望我能得到以下结果;

    col1   col2    col3
0   10     00       00 
1   10     00       01
2   10     00       02
3   10     00       03
4   10     00       04

each rows show the splitted number. 每行显示分割的数字。 I guess the number should be converted to string, but I have no idea next step.... I wanna ask how to split number to separate columns. 我想这个数字应该转换为字符串,但我不知道下一步....我想问一下如何将数字拆分为单独的列。

# make string version of original column, call it 'col'
df['col'] = df['col1'].astype(str)

# make the new columns using string indexing
df['col1'] = df['col'].str[0:2]
df['col2'] = df['col'].str[2:4]
df['col3'] = df['col'].str[4:6]

# get rid of the extra variable (if you want)
df.drop('col', axis=1, inplace=True)

One option is to use extractall() method with regex (\\d{2})(\\d{2})(\\d{2}) which captures every other two digits as columns. 一种选择是使用带有正则表达式(\\d{2})(\\d{2})(\\d{2}) extractall()方法,该方法将每两位数字捕获为列。 ?P<col1> is the name of the captured group which will be converted to the column names: ?P<col1>是将被转换为列名的捕获组的名称:

df.col1.astype(str).str.extractall("(?P<col1>\d{2})(?P<col2>\d{2})(?P<col3>\d{2})").reset_index(drop=True)

#   col1  col2  col3
# 0   10    00    00
# 1   10    00    01
# 2   10    00    02
# 3   10    00    03
# 4   10    00    04

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