如何拆分“数字”以分隔 Pandas DataFrame 中的列
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how to split 'number' to separate columns in pandas DataFrame
提问by Heisenberg
I have a dataframe;
我有一个数据框；
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;
我希望我能得到下面的结果；
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. 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.
每行显示拆分的数字。我想数字应该转换为字符串，但我不知道下一步......我想问如何将数字拆分为单独的列。
回答by benten
# 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)
回答by Psidom
One option is to use extractall()method with regex (\d{2})(\d{2})(\d{2})which captures every other two digits as columns. ?P<col1>is the name of the captured group which will be converted to the column names:
一种选择是使用extractall()带有正则表达式的方法，(\d{2})(\d{2})(\d{2})该方法每隔两位数作为列捕获。?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
