[英]splitting a column into multiple columns with specific name in pandas dataframe
I have following dataframe:我有以下数据框:
pri sec
TOM AB,CD,EF
JACK XY,YZ
HARRY FG
NICK KY,NY,SD,EF,FR
I need following output with column names as following(based on how many , separated fields exists in column 'sec'):我需要以下带有列名的输出(基于列“秒”中存在多少个分隔字段):
pri sec sec0 sec1 sec2 sec3 sec4
TOM AB,CD,EF AB CD EF NaN NaN
JACK XY,YZ XY YZ NaN NaN NaN
HARRY FG FG NaN NaN NaN NaN
NICK KY,NY,SD,EF,FR KY NY SD EF ER
Can I get any suggestions?我能得到任何建议吗?
Use join
+ split
+ add_prefix
:使用
join
+ split
+ add_prefix
:
df = df.join(df['sec'].str.split(',', expand=True).add_prefix('sec'))
print (df)
pri sec sec0 sec1 sec2 sec3 sec4
0 TOM AB,CD,EF AB CD EF None None
1 JACK XY,YZ XY YZ None None None
2 HARRY FG FG None None None None
3 NICK KY,NY,SD,EF,FR KY NY SD EF FR
And if need NaN
s add fillna
:如果需要
NaN
添加fillna
:
df = df.join(df['sec'].str.split(',', expand=True).add_prefix('sec').fillna(np.nan))
print (df)
pri sec sec0 sec1 sec2 sec3 sec4
0 TOM AB,CD,EF AB CD EF NaN NaN
1 JACK XY,YZ XY YZ NaN NaN NaN
2 HARRY FG FG NaN NaN NaN NaN
3 NICK KY,NY,SD,EF,FR KY NY SD EF FR
Try following code (explanations as comments).尝试以下代码(解释为注释)。 It finds max length of items in "sec" column and creates names accordingly:
它在“秒”列中找到项目的最大长度并相应地创建名称:
maxlen = max(list(map(lambda x: len(x.split(",")) ,df.sec))) # find max length in 'sec' column
cols = ["sec"+str(x) for x in range(maxlen)] # create new column names
datalist = list(map(lambda x: x.split(","), df.sec)) # create list from entries in "sec"
newdf = pd.DataFrame(data=datalist, columns=cols) # create dataframe of new columns
newdf = pd.concat([df, newdf], axis=1) # add it to original dataframe
print(newdf)
Output:输出:
pri sec sec0 sec1 sec2 sec3 sec4
0 TOM AB,CD,EF AB CD EF None None
1 JACK XY,YZ XY YZ None None None
2 HARRY FG FG None None None None
3 NICK KY,NY,SD,EF,FR KY NY SD EF FR
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