# 511. Game Play Analysis I

## Description

Table: Activity

+--------------+---------+
| Column Name  | Type    |
+--------------+---------+
| player_id    | int     |
| device_id    | int     |
| event_date   | date    |
| games_played | int     |
+--------------+---------+
(player_id, event_date) is the primary key (combination of columns with unique values) of this table.
This table shows the activity of players of some games.
Each row is a record of a player who logged in and played a number of games (possibly 0) before logging out on someday using some device.


Write a solution to find the first login date for each player.

Return the result table in any order.

The result format is in the following example.

Example 1:

Input:
Activity table:
+-----------+-----------+------------+--------------+
| player_id | device_id | event_date | games_played |
+-----------+-----------+------------+--------------+
| 1         | 2         | 2016-03-01 | 5            |
| 1         | 2         | 2016-05-02 | 6            |
| 2         | 3         | 2017-06-25 | 1            |
| 3         | 1         | 2016-03-02 | 0            |
| 3         | 4         | 2018-07-03 | 5            |
+-----------+-----------+------------+--------------+
Output:
+-----------+-------------+
+-----------+-------------+
| 1         | 2016-03-01  |
| 2         | 2017-06-25  |
| 3         | 2016-03-02  |
+-----------+-------------+


## Solutions

Solution 1: Group By + Min Function

We can use GROUP BY to group the player_id and then take the minimum event_date in each group as the date when the player first logged into the platform.

• import pandas as pd

def game_analysis(activity: pd.DataFrame) -> pd.DataFrame:
return (
activity.groupby("player_id")
.reset_index()
)


• # Write your MySQL query statement below