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Hello, I am trying to transfer over from excel to pandas.
I want to add new column called 'daily_volume' where if the 'project_name' is equal to the above row project_name then calculate the difference.
For example, 1,424.53 - 1,343.68 = 80.85
My goal is to see 80.85 in row 2 under the newly created 'daily_volume' column for $LONDON Gift.
Basically, the first row for a project name will always be blank.
If I get you, the idea is to calculate the difference between the current total_volume and its immediately below taking into account the project_name, right?. You can group your dataframe by project_name column, select the total_volume and after that you can use .diff() method, this method make the operation you need.
| date | total_volume | project_name | |
|---|---|---|---|
| 0 | 2021-08-26 | 1343.68 | \$LONDON Gift |
| 1 | 2021-08-26 | 1424.53 | \$LONDON Gift |
| 2 | 2021-08-26 | 1800.10 | \$LONDON Gift |
| 3 | 2021-08-26 | 2345.23 | \$GROUP_2 |
| 4 | 2021-08-26 | 2500.45 | \$GROUP_2 |
| 5 | 2021-08-26 | 2567.76 | \$GROUP_3 |
You can observe there are 3 different groups: $LONDON Gift, $GROUP_2 and $GROUP_3
We create the new column daily_volume as follow:
df['daily_volume'] = df.groupby('project_name')['total_volume'].diff()
Output:
| date | total_volume | project_name | daily_volume | |
|---|---|---|---|---|
| 0 | 2021-08-26 | 1343.68 | \$LONDON Gift | NaN |
| 1 | 2021-08-26 | 1424.53 | \$LONDON Gift | 80.85 |
| 2 | 2021-08-26 | 1800.10 | \$LONDON Gift | 375.57 |
| 3 | 2021-08-26 | 2345.23 | \$GROUP_2 | NaN |
| 4 | 2021-08-26 | 2500.45 | \$GROUP_2 | 155.22 |
| 5 | 2021-08-26 | 2567.76 | \$GROUP_3 | NaN |
A final recommendation: Avoid to use image as data, put the code you have in the question, something like: pd.DataFrame({...}).
