Question

我有下面的数据集和代码可以正常工作，除了输出中包括周末。我要排除周末。

record_id,date,site,sick,funny,happy
CDEC1947-6,9/2/2018,2,1,1,1
IJKC1953-4,9/29/2018,2,1,1,1
FGHC1724-9,10/25/2018,2,3,1,1
FGHC2929-1,10/31/2018,4,1,1,1
CDEC1912-0,11/1/2018,1,1,1,1
IJKC1726-4,11/2/2018,1,3,1,1
IJKC1728-0,10/26/2018,2,3,1,1
ABCC1730-6,11/2/2018,2,3,1,1
ABCC1731-4,11/2/2018,2,3,1,1
CDEC1733-0,10/22/2018,1,3,1,1
CDEC1735-5,11/2/2018,2,3,1,1
IJKC1914-6,10/27/2018,2,6,1,1
ABCC1916-1,10/23/2018,2,6,1,1
IJKC1918-7,11/2/2018,2,1,1,1
CDEC1920-3,10/24/2018,1,6,1,1
IJKC1943-5,11/2/2018,2,4,1,1
ABCC1945-0,11/2/2018,1,4,1,1
ABCC1949-2,10/25/2018,2,4,1,1
CDEC1951-8,11/2/2018,2,5,1,1
CDEC2924-2,11/3/2018,4,1,1,1
CDEC2927-5,11/3/2018,1,1,1,1
ABCC2925-9,11/4/2018,4,1,1,1
IJKC1941-9,11/4/2018,2,4,1,1
ABCC2922-6,11/5/2018,1,1,1,1

代码：

import pandas as pd
import numpy as np
from plotly.offline import init_notebook_mode, iplot
from plotly.graph_objs import *
import plotly.graph_objs as go
import datetime as dt
#import datetime
#from datetime import date
#from datetime import timedelta
today = date.today()
from IPython.core.interactiveshell import InteractiveShell
%matplotlib inline

df=pd.read_csv("dataset.csv", encoding="utf-8",low_memory=False)

df["date"]=pd.to_datetime(df["date"])
df["site"]=df["site"].astype("category") # Convert to category
df['sick']=df['sick'].astype('category')
df["funny"]=df["funny"].astype("category")
df["happy"]=df["happy"].astype("category")

df = df.sort_values(by='date', ascending='True')
df.head()
df

record_id   date    site    sick    funny   happy
0   CDEC1947-6  2018-09-02  2   1   1   1
1   IJKC1953-4  2018-09-29  2   1   1   1
9   CDEC1733-0  2018-10-22  1   3   1   1
12  ABCC1916-1  2018-10-23  2   6   1   1
14  CDEC1920-3  2018-10-24  1   6   1   1
2   FGHC1724-9  2018-10-25  2   3   1   1
17  ABCC1949-2  2018-10-25  2   4   1   1
6   IJKC1728-0  2018-10-26  2   3   1   1
11  IJKC1914-6  2018-10-27  2   6   1   1
3   FGHC2929-1  2018-10-31  4   1   1   1
4   CDEC1912-0  2018-11-01  1   1   1   1
7   ABCC1730-6  2018-11-02  2   3   1   1
10  CDEC1735-5  2018-11-02  2   3   1   1
5   IJKC1726-4  2018-11-02  1   3   1   1
13  IJKC1918-7  2018-11-02  2   1   1   1
15  IJKC1943-5  2018-11-02  2   4   1   1
16  ABCC1945-0  2018-11-02  1   4   1   1
18  CDEC1951-8  2018-11-02  2   5   1   1
8   ABCC1731-4  2018-11-02  2   3   1   1
19  CDEC2924-2  2018-11-03  4   1   1   1
20  CDEC2927-5  2018-11-03  1   1   1   1
22  IJKC1941-9  2018-11-04  2   4   1   1
21  ABCC2925-9  2018-11-04  4   1   1   1
23  ABCC2922-6  2018-11-05  1   1   1   1

# get first and last datetime for final week of data
range_max = df['date'].max()
range_min = range_max - dt.timedelta(days=7)

# take slice with final week of data
sliced_df = df[(df['date'] >= range_min) & 
               (df['date'] <= range_max)]

sliced_df

record_id   date    site    sick    funny   happy
3   FGHC2929-1  2018-10-31  4   1   1   1
4   CDEC1912-0  2018-11-01  1   1   1   1
7   ABCC1730-6  2018-11-02  2   3   1   1
10  CDEC1735-5  2018-11-02  2   3   1   1
5   IJKC1726-4  2018-11-02  1   3   1   1
13  IJKC1918-7  2018-11-02  2   1   1   1
15  IJKC1943-5  2018-11-02  2   4   1   1
16  ABCC1945-0  2018-11-02  1   4   1   1
18  CDEC1951-8  2018-11-02  2   5   1   1
8   ABCC1731-4  2018-11-02  2   3   1   1
19  CDEC2924-2  2018-11-03  4   1   1   1
20  CDEC2927-5  2018-11-03  1   1   1   1
22  IJKC1941-9  2018-11-04  2   4   1   1
21  ABCC2925-9  2018-11-04  4   1   1   1
23  ABCC2922-6  2018-11-05  1   1   1   1

如何删除周末？（2018-11-04和2018-11-03）在输出中？我正在考虑使用timedelta工作日<= 4，但是我不知道如何在这里申请。非常欢迎您的帮助。

Answer 1

您已经走对了。您可以使用.dt accessor来检索带有日期时间的数据框列的工作日。然后可以将其用于过滤数据框行：

filtered_df = sliced_df[sliced_df['date'].dt.weekday < 5]

过滤日期范围（不包括周末）

1 个答案: