GROUP BY
HAVING
と同じ処理を行う 2021-07-26
## BSSID毎の出現回数を算出する
appearances = 10
countBSSID = df[["BSSID", "SSID"]].groupby(["BSSID"]).filter(lambda x: x["SSID"].count() > appearances)
countBSSID = countBSSID.groupby(["BSSID"]).count().to_dict()["SSID"]
countBSSID = pd.DataFrame(list(countBSSID.items())).rename({0: "BSSID", 1: "COUNT"})
display(countBSSID)
BSSID COUNT
0 00:05:B5:4D:04:A8 13
1 00:05:B5:96:AB:D4 18
2 00:05:B5:E6:11:F9 39
3 00:1A:EB:C9:BF:00 11461
4 00:1A:EB:C9:BF:01 21935
... ... ...
217 FA:8F:CA:95:0E:DF 11
218 FA:B7:97:00:90:7B 25
219 FC:62:B9:75:3E:68 53
220 FC:87:43:01:55:31 78
221 FE:46:D7:20:10:9B 13
222 rows × 2 columns
Pandas
Python
DataFrame
GROUP BY
HAVING
GitHub Copilot のドキュメント
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Apr 5, 2025.github/copilot-instructions.md ファイルに Markdown 形式で指示を記述します。
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