Create a day-of-week column in a Pandas dataframe using Python

Create a day-of-week column in a Pandas dataframe using Python

I’d like to read a csv file into a pandas dataframe, parse a column of dates from string format to a date object, and then generate a new column that indicates the day of the week.

This is what I’m trying:

What I’d like to do is something like:

import pandas as pd

import csv

df = pd.read_csv('data.csv', parse_dates=['date']))

df['day-of-week'] = df['date'].weekday()


AttributeError: 'Series' object has no attribute 'weekday'

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Thank you for your help. James

Pandas 0.23+

Use pandas.Series.dt.day_name(), since pandas.Timestamp.weekday_name has been deprecated:

import pandas as pd


df = pd.DataFrame({'my_dates':['2015-01-01','2015-01-02','2015-01-03'],'myvals':[1,2,3]})
df['my_dates'] = pd.to_datetime(df['my_dates'])

df['day_of_week'] = df['my_dates'].dt.day_name()

Output:

    my_dates  myvals day_of_week
0 2015-01-01       1    Thursday
1 2015-01-02       2      Friday
2 2015-01-03       3    Saturday

Pandas 0.18.1+

As user jezrael points out below, dt.weekday_name was added in version 0.18.1 Pandas Docs

import pandas as pd

df = pd.DataFrame({'my_dates':['2015-01-01','2015-01-02','2015-01-03'],'myvals':[1,2,3]})
df['my_dates'] = pd.to_datetime(df['my_dates'])
df['day_of_week'] = df['my_dates'].dt.weekday_name

Output:

    my_dates  myvals day_of_week
0 2015-01-01       1    Thursday
1 2015-01-02       2      Friday
2 2015-01-03       3    Saturday

Original Answer:

Use this:

http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.dt.dayofweek.html

See this:

https://stackoverflow.com/questions/28009370/get-weekday-for-datetime-in-pandas-dataframe

If you want a string instead of an integer do something like this:

import pandas as pd

df = pd.DataFrame({'my_dates':['2015-01-01','2015-01-02','2015-01-03'],'myvals':[1,2,3]})
df['my_dates'] = pd.to_datetime(df['my_dates'])
df['day_of_week'] = df['my_dates'].dt.dayofweek

days = {0:'Mon',1:'Tues',2:'Weds',3:'Thurs',4:'Fri',5:'Sat',6:'Sun'}

df['day_of_week'] = df['day_of_week'].apply(lambda x: days[x])

Output:

    my_dates  myvals day_of_week
0 2015-01-01       1       Thurs
1 2015-01-02       2         Fri
2 2015-01-01       3       Thurs

In version 0.18.1 is added dt.weekday_name:

print df
    my_dates  myvals
0 2015-01-01       1
1 2015-01-02       2
2 2015-01-03       3

print df.dtypes
my_dates    datetime64[ns]
myvals               int64
dtype: object

df['day_of_week'] = df['my_dates'].dt.weekday_name()
print df
    my_dates  myvals day_of_week
0 2015-01-01       1    Thursday
1 2015-01-02       2      Friday
2 2015-01-03       3    Saturday

Another solution with assign:

print df.assign(day_of_week = df['my_dates'].dt.weekday_name())
    my_dates  myvals day_of_week
0 2015-01-01       1    Thursday
1 2015-01-02       2      Friday
2 2015-01-03       3    Saturday

df =df['Date'].dt.dayofweek

dayofweek is in numeric format

Using dt.weekday_name is deprecated since pandas 0.23.0, instead, use dt.day_name():

df = pd.DataFrame({'my_dates':['2015-01-01','2015-01-02','2015-01-03'],'myvals':[1,2,3]})
df['my_dates'] = pd.to_datetime(df['my_dates'])

df['my_dates'].dt.day_name()

0    Thursday
1      Friday
2    Saturday
Name: my_dates, dtype: object

Just in case if .dt doesn't work for you. Trying .DatetimeIndex might help. Hope the code and our test result here help you fix it. Regards,

import pandas as pd
import datetime

df = pd.DataFrame({'Date':['2015-01-01','2015-01-02','2015-01-03'],'Number':[1,2,3]})

df['Day'] = pd.DatetimeIndex(df['Date']).day_name() # week day name
df.head()

When date is the index

…and only the first three letters are required:

df['day'] = df.index.day_name().str[:3]

data['Day_Of_Week'] = pd.DatetimeIndex(data['Birth_Date']).day_name()

Command appends new column/feature as data['Day_Of-Week'] from data['Birth_Date'] column which is present in dataset/csv previously.