使用日期星期和数据行内容重命名多列

问题描述

我有一个宽数据格式的数据框，其中日期范围和空字符串作为列名，但是第一行具有一些预期的列标题，因此我需要一个代码，从标题中推断出星期，然后从列中选择列名。第一行并将其重命名（即week1_quantity，week1_sales，week1_profit）

import pandas as pd
df = pd.DataFrame([
    {'Related Fields':'Description','Unnamed 1':'barcode','Unnamed 2':'department','Unnamed 3':'section','Unnamed 4':'reference','Sales: (06/07/2020,12/07/2020)':'Quantity','Unnamed 6':'amount','Unnamed 7':'cost','Unnamed 8':'% M/S','Unnamed 9': 'profit','Sales: (29/06/2020,05/07/2020)': 'Quantity','Unnamed 11':'amount','Unnamed 12':'cost','Unnamed 13':'% M/S','Unnamed 14':'profit'},{'Related Fields':'cornflakes','Unnamed 1':'0001198','Unnamed 2':'grocery','Unnamed 3':'breakefast','Unnamed 4': '0001198',12/07/2020)': 60,'Unnamed 6': 6000,'Unnamed 7':3000,'Unnamed 8':50,'Unnamed 9':3000,05/07/2020)': 120,'Unnamed 11':12000,'Unnamed 12':6000,'Unnamed 13':50,'Unnamed 14':6000}
])

预期结果

df2 = pd.DataFrame([
    {'Description':'cornflakes','barcode':'0001198','department':'grocery','section':'breakefast','reference':'0001198','week28_quantity':60,'week28_amount':6000,'week28_cost':3000,'week28_% M/S':50,'week28_profit':3000,'week29_quantity':120,'week29_amount':6000,'week29_cost':6000,'week29_% M/S':50,'week28_profit':6000}
])

我试图手动更改名称，但是想要一个自动解决方案。

解决方法

您可以通过使用datetime.strptime解析日期并使用datetime.isocalendar来获取星期数来解决问题。

from datetime import datetime

# get week numbers
wknums = [
    'week' + str(
        datetime.strptime(colname.split()[1][1:11],'%d/%m/%Y')
        .isocalendar()[1]
    ) + '_'
    if colname.startswith('Sales')
    else None
    for colname in df.columns
]

wknums = (
    pd.Series(wknums).ffill().fillna('') # forward fill week numbers
    + df.loc[0].to_numpy() # add text from first row
).str.lower() # change to lower case,use it only if it helps


df.columns = wknums # replace df column labels
df = df.iloc[1:].reset_index(drop=True) # drop first row

输出

df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 1 entries,0 to 0
Data columns (total 15 columns):
 #   Column           Non-Null Count  Dtype
---  ------           --------------  -----
 0   description      1 non-null      object
 1   barcode          1 non-null      object
 2   department       1 non-null      object
 3   section          1 non-null      object
 4   reference        1 non-null      object
 5   week28_quantity  1 non-null      object
 6   week28_amount    1 non-null      object
 7   week28_cost      1 non-null      object
 8   week28_% m/s     1 non-null      object
 9   week28_profit    1 non-null      object
 10  week27_quantity  1 non-null      object
 11  week27_amount    1 non-null      object
 12  week27_cost      1 non-null      object
 13  week27_% m/s     1 non-null      object
 14  week27_profit    1 non-null      object
dtypes: object(15)
memory usage: 248.0+ bytes