How to Calculate Score Differences for Multiple Websites and Countries in Pandas?

Grouping and Finding Differences in Multiple Fields with Pandas

In working with datasets, it is often necessary to compute differences or changes between values over time or across different categories. In Pandas, you can efficiently perform these calculations by utilizing the groupby() and diff() functions.

In the given scenario, you have a DataFrame with data on various websites and their scores in different countries. Your goal is to determine the 1/3/5-day score difference for each site country combination.

Dataframe Sorting and Grouping

To begin, sort your DataFrame by the site, country, and date columns. Sorting ensures that similar data points are grouped together, making it easier to calculate differences.

<code class="python">df = df.sort_values(by=['site', 'country', 'date'])</code>

Next, use the groupby() function to group the data by site and country.

<code class="python">grouped = df.groupby(['site', 'country'])</code>

Calculating Differences

With the data grouped, you can now calculate the score differences using the diff() function. This function computes the difference between consecutive rows in a group.

<code class="python">df['diff'] = grouped['score'].diff().fillna(0)</code>

The diff() function fills missing values with 0 by default, ensuring a consistent and complete dataset.

Resulting Dataframe

The resulting DataFrame will contain the original data along with the calculated score differences:

         date    site country  score  diff
8  2018-01-01      fb      es    100   0.0
9  2018-01-02      fb      gb    100   0.0
5  2018-01-01      fb      us     50   0.0
6  2018-01-02      fb      us     55   5.0
7  2018-01-03      fb      us    100  45.0
1  2018-01-01  google      ch     50   0.0
4  2018-01-02  google      ch     10 -40.0
0  2018-01-01  google      us    100   0.0
2  2018-01-02  google      us     70 -30.0
3  2018-01-03  google      us     60 -10.0

This DataFrame provides the desired 1/3/5-day score difference for each site/country combination.

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