Question

我试图用空格分隔符将熊猫数据框中的一列拆分为多个。我意识到某些行具有日期字段，因此与没有日期字段的行相比，它需要额外的列。这是列值的示例，

DA Firstname Lastname 09/30/2020 07:44 AM 9/23/2020 6:06:38 PM
JW Firstname Lastname 10/25/2020 11:06 AM None

第一行不适合使用空格分隔符，因为有8个空格。第二行适用于我的数据集，因为会有6个空格。反正有将日期结合在一起作为分隔符吗？

[“ Inital”，“ Firstname”，“ lastname”，“ date / time1”，“ date / time2”]，其中“ date / time2”列也可以包含“ None”

我尝试使用的代码是

dataset= pd.read_csv("newOutput6",encoding = "ISO-8859-1", delimiter="\t", names = ['Name','Date'], index=False)
tmpDF = pd.DataFrame(columns=['Initals','FName','LName','SignupTime','Waiver'])
tmpDF[['Initals','FName','LName','SignupTime','Waiver']] = dataset['Name'].str.split(' ', expand=True)

示例csv：

 ,Name,Date
0,MA FName LName 10/25/2020 09:40 PM None,"October 26, 2020,8:00AM Until 8:50AM "
1,JB FName LName 10/26/2020 07:19 AM None,"October 26, 2020,8:00AM Until 8:50AM "
2,TB FName LName 10/25/2020 09:03 PM None,"October 26, 2020,8:00AM Until 8:50AM "
3,MB FName LName 10/25/2020 09:40 PM None,"October 26, 2020,8:00AM Until 8:50AM "
4,NC FName LName 10/25/2020 10:17 PM None,"October 26, 2020,8:00AM Until 8:50AM "
5,AC FName LName 10/25/2020 09:23 PM None,"October 26, 2020,8:00AM Until 8:50AM "
6,NF FName LName 10/26/2020 07:56 AM None,"October 26, 2020,8:00AM Until 8:50AM "
7,BG FName LName 10/25/2020 10:41 PM None,"October 26, 2020,8:00AM Until 8:50AM "
8,GH FName LName 10/26/2020 07:39 AM None,"October 26, 2020,8:00AM Until 8:50AM "
9,EH FName LName 10/25/2020 10:06 PM None,"October 26, 2020,8:00AM Until 8:50AM "
10,DM FName LName 10/25/2020 11:42 PM None,"October 26, 2020,8:00AM Until 8:50AM "
11,JM FName LName 10/25/2020 09:24 PM None,"October 26, 2020,8:00AM Until 8:50AM "
12,TP FName LName 10/26/2020 12:32 AM None,"October 26, 2020,8:00AM Until 8:50AM "
13,DS FName LName 10/25/2020 11:12 PM None,"October 26, 2020,8:00AM Until 8:50AM "
14,KS FName LName 10/25/2020 07:46 PM None,"October 26, 2020,8:00AM Until 8:50AM "
15,JW FName LName 10/25/2020 11:06 AM None,"October 26, 2020,8:00AM Until 8:50AM "
16,DA FName LName 09/30/2020 07:44 AM 9/23/2020 6:06:38 PM,"October 26, 2020,9:00AM Until 9:50AM "

索引16是不遵循传统格式的行，我怀疑需要使用正则表达式来确定它。

Answer 1

在“名字”和“姓氏”中没有空格的情况下（否则您将无法区分它们）：

pattern = ('^(?P<Initials>\w+)\s'
           + '(?P<FName>\w+)\s'
           + '(?P<LName>\w+)\s'
           + '(?P<SignupTime>\d+/\d+/\d+ \d+:\d+ \w+)\s'
           + '(?P<Waiver>.*)'
)

df['name'].str.extract(pattern)

输出：

  Initials      FName     LName           SignupTime                Waiver
0       DA  Firstname  Lastname  09/30/2020 07:44 AM  9/23/2020 6:06:38 PM
1       JW  Firstname  Lastname  10/25/2020 11:06 AM                  None

更新：对于可选的缩写，您可以尝试以下模式：

pattern = ('^(?P<Initials>\w+\s)?'    # make initial optional
           + '(?P<FName>\w+)\s+'
           + '(?P<LName>\w+)\s+'
           + '(?P<SignupTime>\d+/\d+/\d+ \d+:\d+ \w+)\s'
           + '(?P<Waiver>.*)'
)

请注意，现在如果存在Initials，将有一个尾随空格，您可以轻松处理。

用定界符分割熊猫列，行中有两个不同的大小

1 个答案: