Hi StackOverflow community,
I have a data frame consisting of datetime dates from 2010-01-04 to 2020-01-01. Here is a small random snippet:
28 2010-01-04 0.70930 LVL
29 2010-01-04 1.58850 AUD
30 2010-01-04 26.28500 CZK
31 2010-01-04 1.49530 CAD
32 2010-01-04 11.16080 HKD
33 2010-01-05 1645.74000 KRW
34 2010-01-05 0.90045 GBP
35 2010-01-05 15.64660 EEK
36 2010-01-05 18.48330 MXN
37 2010-01-05 1.44420 USD
38 2010-01-05 10.50690 ZAR
How can I create a new "Day of the Week" column for each observation? For example,
28 2010-01-04 0.70930 LVL Monday
29 2010-01-04 1.58850 AUD Monday
30 2010-01-04 26.28500 CZK Monday
31 2010-01-04 1.49530 CAD Monday
32 2010-01-04 11.16080 HKD Monday
33 2010-01-05 1645.74000 KRW Tuesday
34 2010-01-05 0.90045 GBP Tuesday
35 2010-01-05 15.64660 EEK Tuesday
36 2010-01-05 18.48330 MXN Tuesday
37 2010-01-05 1.44420 USD Tuesday
38 2010-01-05 10.50690 ZA Tuesday
Thank you all for any guidance.
Tony
Here is the code to my project:
import matplotlib.pyplot as plt
import numpy as np
import scipy.stats as sp
start_date = "2010-01-01"
end_date = "2020-01-01"
symbol = "GBP"
resp = requests.get('https://api.exchangeratesapi.io/history?start_at={}&end_at={}&base=EUR'.format(start_date, end_date))
if resp.status_code != 200:
# This means something went wrong.
raise ApiError('GET /tasks/ {}'.format(resp.status_code))
data = resp.json()
df2 = json_normalize(data)
df2.drop(["start_at","base","end_at"],axis=1,inplace=True)
df2.columns = [col.replace('rates.', '') for col in df2.columns]
df3 = df2.stack().reset_index().drop('level_0',axis=1)
df3.columns = ['Date', 'FXRateEUR']
df3['Date'], df3['Symbol'] = df3['Date'].str.split('.', 1).str
df3['Date'] = df3['Date'].astype(str) + " " + '00:00:00'
df3['Date'] = pd.to_datetime(df3['Date'])
df3 = df3.sort_values(by='Date').reset_index(drop=True)
df3.head(50)
you can use day_name
df3['Day of the Week'] = pd.to_datetime(df3['Date']).dt.day_name()