如何在pandas dataframe中将yyyymmdd格式转换为mm-dd-yyyy？

Question

我试图用列incident history（例如Class II:O:20181119）yyyymmdd重新格式化为数据帧中的mm dd yyyyy，但需要注意的是，有些单元格与具有多个类的某些单元格不相等

我尝试过使用“分割并应用”，但我无法将其操纵到可以清理的程度

import pandas as pd
df = pd.read_excel('C:/Users/blablabla')

我试过这样做，但它只输出NaN：

^{pr2}$

也尝试过，但得到了TypeError: ("'float' object is not iterable", 'occurred at index 0')

def foo(c):
   for x in c['incident history']:
       return x        
df['incident history reformed'] = df.apply(foo, axis=1)
print (df['incident history reformed'])

Answer 1

我已经尽量使它可读。 您的日期似乎总是列中的最后8个字符Incident history。你可以按你所做的选择它们。我用负指数。在

然后我使用to_datetime(doc)将string类型的列转换为datetime

要对数据帧进行排序，可以使用sort_values，方法是精确地对列进行排序(doc)

df = pd.DataFrame([
                   ["Class II : R : 20180920"],
                   ["Class II : O : 20181109"],
                   ["Class O : D1 : 20170601"],
                   ["Class O : D1 : 20190219"]],
                  columns=["Incident history"])

print(df)
#        Incident history
# 0  Class II: R: 20180920
# 1  Class II: O: 20181109
# 2  Class O: D1: 20170601
# 3  Class O: D1: 20190219

# Create a string variable containing the date
df["date"] = df["Incident history"].str[-8:]
print(df)
#         Incident history date_string
# 0  Class II: R: 20180920    20180920
# 1  Class II: O: 20181109    20181109
# 2  Class O: D1: 20170601    20170601
# 3  Class O: D1: 20190219    20190219

# Transform the date column to the type "date"
df["date"] = pd.to_datetime(df["date"], format="%Y%m%d", yearfirst=True)
print(df)
#         Incident history       date
# 0  Class II: R: 20180920 2018-09-20
# 1  Class II: O: 20181109 2018-11-09
# 2  Class O: D1: 20170601 2017-06-01
# 3  Class O: D1: 20190219 2019-02-19

# Sort according to date
df = df.sort_values(by='date')
print(df)
#         Incident history       date
# 2  Class O: D1: 20170601 2017-06-01
# 0  Class II: R: 20180920 2018-09-20
# 1  Class II: O: 20181109 2018-11-09
# 3  Class O: D1: 20190219 2019-02-19

# Optional : remove the date from "Incident history"
df["Incident history"] = df["Incident history"].str[:-10]
print(df)
# Incident history       date
# 2    Class O: D1  2017-06-01
# 0    Class II: R  2018-09-20
# 1    Class II: O  2018-11-09
# 3    Class O: D1  2019-02-19