Monthly approved spend
mediumMonthly approved spend
Visa Pandas Interview Question
Visa's issuer reports show approved card spend per month and how it changed from the month before.
Use the card_transactions DataFrame and count approved transactions only. Return each month as a string like "2024-01", the total spend as approved_spend, rounded to 2 decimal places, and the percentage change from the previous month as pct_change, rounded to 1 decimal place. The first month has no previous month, so leave its change empty. Sort the rows by month. Assign the answer to result.
Asked of
- Data Analyst
- Product Analyst
- Business Analyst
- Analytics Engineer
- Data Scientist
card_transactionsDataFrame18 rows
| Column Name | Type |
|---|---|
| transaction_id | int64 |
| card_id | int64 |
| merchant_country | str |
| merchant_category | str |
| amount_usd | float64 |
| transaction_date | str |
| status | str |
card_transactionsExample Input
| transaction_id | card_id | merchant_country | merchant_category | amount_usd | transaction_date | status |
|---|---|---|---|---|---|---|
| 3001 | 1 | United States | Groceries | 84.2 | 2024-01-04 | approved |
| 3002 | 2 | France | Travel | 640 | 2024-01-09 | approved |
| 3003 | 3 | Canada | Restaurants | 52.75 | 2024-01-15 | approved |
| 3004 | 4 | Spain | Travel | 410.3 | 2024-01-21 | declined |
| 3005 | 6 | Japan | Electronics | 1299 | 2024-01-28 | approved |
| 3006 | 5 | Canada | Groceries | 96.4 | 2024-02-02 | approved |
| 3007 | 1 | Mexico | Travel | 275 | 2024-02-08 | approved |
| 3008 | 3 | United States | Electronics | 899.99 | 2024-02-13 | approved |
| 3009 | 2 | United States | Restaurants | 68.1 | 2024-02-17 | approved |
| 3010 | 4 | United Kingdom | Groceries | 58.6 | 2024-02-22 | approved |
| 3011 | 6 | United States | Travel | 520 | 2024-02-27 | declined |
Example Output
| month | approved_spend | pct_change |
|---|---|---|
| 2024-01 | 2075.95 | NULL |
| 2024-02 | 1398.09 | -32.7 |
Explanation
January's approved spend is 2,075.95. The declined transaction that month is not counted. February's approved spend is 1,398.09, which is 32.7% lower than January, so its change is -32.7.
The example above is a small slice of the data. Your code runs against the full DataFrames.
Company
Visa
Difficulty
medium
Topic
dates
Language
Pandas
Your code
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