Extracting day of week and hour in Pandas - Step-by-Step Execution

Concept Flow - Extracting day of week and hour

Start with datetime column

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Extract day of week

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Extract hour

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Add new columns to DataFrame

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Use extracted info for analysis

We start with a datetime column, extract the day of week and hour, then add these as new columns for easier analysis.

Execution Sample

Pandas

import pandas as pd

df = pd.DataFrame({'date': pd.to_datetime(['2024-06-01 08:30', '2024-06-02 15:45'])})
df['day_of_week'] = df['date'].dt.day_name()
df['hour'] = df['date'].dt.hour
print(df)

This code creates a DataFrame with datetime values, extracts the day name and hour, and adds them as new columns.

Execution Table

Step	Action	Input	Output
1	Create DataFrame with datetime	['2024-06-01 08:30', '2024-06-02 15:45']	DataFrame with 'date' column as datetime
2	Extract day of week	df['date']	['Saturday', 'Sunday']
3	Add 'day_of_week' column	['Saturday', 'Sunday']	DataFrame with 'day_of_week' column
4	Extract hour	df['date']	[8, 15]
5	Add 'hour' column	[8, 15]	DataFrame with 'hour' column
6	Print final DataFrame	DataFrame with all columns	date day_of_week hour 2024-06-01 08:30:00 Saturday 8 2024-06-02 15:45:00 Sunday 15

💡 All datetime values processed, new columns added successfully.

Variable Tracker

Variable	Start	After Step 1	After Step 3	After Step 5	Final
df	empty	date column with datetime	added day_of_week column	added hour column	final DataFrame with date, day_of_week, hour

Key Moments - 2 Insights

Why do we use dt.day_name() instead of just day?

dt.day_name() gives the weekday name like 'Monday', 'Tuesday' which is easier to read, as shown in execution_table step 2 and 3.

What type of data is in the 'hour' column?

The 'hour' column contains integers representing the hour part of the datetime, as seen in execution_table step 4 and 5.

Visual Quiz - 3 Questions

Look at the execution table, what is the output of extracting day of week at step 2?

A [8, 15]

B ['Monday', 'Tuesday']

C ['Saturday', 'Sunday']

D ['2024-06-01', '2024-06-02']

💡 Hint

Check the 'Output' column in execution_table row for step 2.

At which step is the 'hour' column added to the DataFrame?

A Step 3

B Step 5

C Step 4

D Step 6

💡 Hint

Look for the action 'Add hour column' in execution_table.

If the datetime was '2024-06-01 23:59', what would the 'hour' value be?

A 23

B 59

C 0

D 12

💡 Hint

Refer to how hour is extracted in execution_table step 4.

Concept Snapshot

Use pandas dt accessor to extract parts of datetime:
- day_of_week = df['date'].dt.day_name() gives weekday name
- hour = df['date'].dt.hour gives hour as integer
Add these as new columns for easy analysis.

Full Transcript

We start with a DataFrame containing datetime values. Using pandas dt accessor, we extract the day of week as a name string and the hour as an integer. These are added as new columns to the DataFrame. This helps us analyze data by weekday or hour easily. The execution table shows each step: creating the DataFrame, extracting day names, adding the column, extracting hours, adding that column, and printing the final DataFrame. Variables change as columns are added. Common confusions include why day_name() is used and what data type hour is. The quiz tests understanding of these steps and outputs.