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Merged
merged 10 commits into from
Oct 27, 2023
Merged

feat: add pandas solution to lc problem: No.0550 #1891

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0049de3
Solution for 511.
nrhitik Oct 27, 2023
58d0f05
Solution for 550.
nrhitik Oct 27, 2023
13b2062
Merge branch 'doocs:main' into dev/550
nrhitik Oct 27, 2023
c34f235
Update README.md
nrhitik Oct 27, 2023
6fb99be
Update README_EN.md
nrhitik Oct 27, 2023
1c43401
Update Solution.py
nrhitik Oct 27, 2023
4f4b305
Update Solution.py
nrhitik Oct 27, 2023
88d77cb
Update README_EN.md
nrhitik Oct 27, 2023
ece3671
Update README.md
nrhitik Oct 27, 2023
088ee3c
Merge branch 'main' into dev/550
nrhitik Oct 27, 2023
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18 changes: 18 additions & 0 deletions solution/0500-0599/0550.Game Play Analysis IV/README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -107,4 +107,22 @@ FROM T
WHERE rk = 1;
```

### **Pandas**

```python
import pandas as pd


def gameplay_analysis(activity: pd.DataFrame) -> pd.DataFrame:
activity["first"] = activity.groupby("player_id").event_date.transform(min)
activity_2nd_day = activity[
activity["first"] + pd.DateOffset(1) == activity["event_date"]
]

return pd.DataFrame(
{"fraction": [round(len(activity_2nd_day) / activity.player_id.nunique(), 2)]}
)

```

<!-- tabs:end -->
18 changes: 18 additions & 0 deletions solution/0500-0599/0550.Game Play Analysis IV/README_EN.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -102,4 +102,22 @@ FROM T
WHERE rk = 1;
```

### **Pandas**

```python
import pandas as pd


def gameplay_analysis(activity: pd.DataFrame) -> pd.DataFrame:
activity["first"] = activity.groupby("player_id").event_date.transform(min)
activity_2nd_day = activity[
activity["first"] + pd.DateOffset(1) == activity["event_date"]
]

return pd.DataFrame(
{"fraction": [round(len(activity_2nd_day) / activity.player_id.nunique(), 2)]}
)

```

<!-- tabs:end -->
12 changes: 12 additions & 0 deletions solution/0500-0599/0550.Game Play Analysis IV/Solution.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,12 @@
import pandas as pd


def gameplay_analysis(activity: pd.DataFrame) -> pd.DataFrame:
activity["first"] = activity.groupby("player_id").event_date.transform(min)
activity_2nd_day = activity[
activity["first"] + pd.DateOffset(1) == activity["event_date"]
]

return pd.DataFrame(
{"fraction": [round(len(activity_2nd_day) / activity.player_id.nunique(), 2)]}
)