8. Datetime

57KB
bakery_sales.csv
Open

  1. Load the data and display.

Solution
import pandas as pd
df=pd.read_csv('bakery_sales.csv')
df

# Output
        datetime		total
0	11-07-2019 15:35	23800.0
1	11-07-2019 16:10	15800.0
2	12-07-2019 11:49	58000.0
3	13-07-2019 13:19	14800.0
4	13-07-2019 13:22	15600.0
...	...	...	...
2415	02-05-2020 11:37	19500.0
2416	02-05-2020 11:39	19800.0
2417	02-05-2020 12:15	14300.0
2418	02-05-2020 13:45	15000.0
2419	02-05-2020 14:45	24100.0
2420 rows × 3 columns

  1. Convert the datetime column into proper datetime format, considering the data in the column is in (dd-mm-yyyy hh:mm) format.

Solution
df['datetime']=pd.to_datetime(df['datetime'],format="%d-%m-%Y %H:%M")
df

# Output

        datetime		total
0	2019-07-11 15:35:00	23800.0
1	2019-07-11 16:10:00	15800.0
2	2019-07-12 11:49:00	58000.0
3	2019-07-13 13:19:00	14800.0
4	2019-07-13 13:22:00	15600.0
...	...	...	...
2415	2020-05-02 11:37:00	19500.0
2416	2020-05-02 11:39:00	19800.0
2417	2020-05-02 12:15:00	14300.0
2418	2020-05-02 13:45:00	15000.0
2419	2020-05-02 14:45:00	24100.0
2420 rows × 3 columns

  1. Separate day, month name, and year in different columns from datetime.

Solution
df['date']=df['datetime'].dt.date
df['time']=df['datetime'].dt.time
df

# Output
        datetime		total	date	        time
0	2019-07-11 15:35:00	23800.0	2019-07-11	15:35:00
1	2019-07-11 16:10:00	15800.0	2019-07-11	16:10:00
2	2019-07-12 11:49:00	58000.0	2019-07-12	11:49:00
3	2019-07-13 13:19:00	14800.0	2019-07-13	13:19:00
4	2019-07-13 13:22:00	15600.0	2019-07-13	13:22:00
...	...	...	...	...	...
2415	2020-05-02 11:37:00	19500.0	2020-05-02	11:37:00
2416	2020-05-02 11:39:00	19800.0	2020-05-02	11:39:00
2417	2020-05-02 12:15:00	14300.0	2020-05-02	12:15:00
2418	2020-05-02 13:45:00	15000.0	2020-05-02	13:45:00
2419	2020-05-02 14:45:00	24100.0	2020-05-02	14:45:00

  1. Separate date, month and year from date column.

Solution

  1. Extract time from the datetime column.

Solution

  1. Create a sample of 700 rows from the dataset and find the oldest date in the dataset.

Solution

  1. Create a sample of 700 rows from the dataset and find the latest date in the dataset.

Solution

  1. Create a sample of 700 rows from the dataset and arrange them in ascending order on behalf of date.

Solution

  1. Display the data of the sale that happened between 1st Aug 2019 and 01 Dec 2019.

Solution

  1. Find out the total sales on each date.

Solution

  1. Find out total sale on each day.

Solution

  1. Find rows where the transaction happened in the afternoon (12 PM - 6 PM)

Solution

  1. Find the sale happened on weekends(sat and sun).

Solution

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