質問編集履歴
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### 前提・実現したいこと
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csvファイルを読み込み、そこからpandasにおけるgroupby()メソッドを利用して国のコードが"JP"のみのデータの平均値をとり、それをグラフ化したいのですがgroupbyを使用するところでエラーが発生しました。
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もう一度考え直したいので白紙にさせてください
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```
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KeyError Traceback (most recent call last)
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<ipython-input-10-5bf405663c72> in <module>()
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21 import plotly_express as px
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---> 22 df_melt = df.melt(id_vars='date', value_vars=["小売・娯楽", "食料品店・薬局", "公園", "乗換駅", "職場", "住宅"])
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23 fig = px.line(df_melt, x="date", y="value", color='variable',
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24 title="Google Mobility Report")
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7 frames
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/usr/local/lib/python3.6/dist-packages/pandas/core/indexing.py in _validate_read_indexer(self, key, indexer, axis, raise_missing)
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1653 if not (ax.is_categorical() or ax.is_interval()):
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1654 raise KeyError(
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-> 1655 "Passing list-likes to .loc or [] with any missing labels "
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1656 "is no longer supported, see "
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1657 "https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#deprecate-loc-reindex-listlike" # noqa:E501
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KeyError: 'Passing list-likes to .loc or [] with any missing labels is no longer supported, see https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#deprecate-loc-reindex-listlike'
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```
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### 該当のソースコード
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```Python
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import pandas as pd
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# Google's COVID-19 Community Mobility Reports (COVID-19 コミュニティ モビリティ レポート) の読み込み
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df = pd.read_csv("/content/drive/My Drive/Global_Mobility_Report.csv", encoding="utf-8")
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df = df.rename(columns={'retail_and_recreation_percent_change_from_baseline':'小売・娯楽',
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'grocery_and_pharmacy_percent_change_from_baseline': '食料品店・薬局',
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'parks_percent_change_from_baseline': '公園',
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'transit_stations_percent_change_from_baseline': '乗換駅',
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'workplaces_percent_change_from_baseline': '職場',
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'residential_percent_change_from_baseline': '住宅'})
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# 日本のデータのみ絞り込む (# データ数 = 6240件)
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#print(df.info())
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grp = df.groupby('country_region_code').mean()
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df = grp.query('country_region_code == "JP"')
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import plotly_express as px
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df_melt = df.melt(id_vars='date', value_vars=["小売・娯楽", "食料品店・薬局", "公園", "乗換駅", "職場", "住宅"])
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fig = px.line(df_melt, x="date", y="value", color='variable',
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title="Google Mobility Report")
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fig.show()
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```
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文法の修正
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### 発生している問題・エラーメッセージ
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```
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/usr/local/lib/python3.6/dist-packages/pandas/core/groupby/grouper.py in get_grouper(obj, key, axis, level, sort, observed, mutated, validate)
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KeyError Traceback (most recent call last)
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599 else:
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-->
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<ipython-input-10-5bf405663c72> in <module>()
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21 import plotly_express as px
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---> 22 df_melt = df.melt(id_vars='date', value_vars=["小売・娯楽", "食料品店・薬局", "公園", "乗換駅", "職場", "住宅"])
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23 fig = px.line(df_melt, x="date", y="value", color='variable',
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24 title="Google Mobility Report")
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602 # Add key to exclusions
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7 frames
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/usr/local/lib/python3.6/dist-packages/pandas/core/indexing.py in _validate_read_indexer(self, key, indexer, axis, raise_missing)
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1653 if not (ax.is_categorical() or ax.is_interval()):
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1654 raise KeyError(
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-> 1655 "Passing list-likes to .loc or [] with any missing labels "
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1656 "is no longer supported, see "
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1657 "https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#deprecate-loc-reindex-listlike" # noqa:E501
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KeyError: 'Passing list-likes to .loc or [] with any missing labels is no longer supported, see https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#deprecate-loc-reindex-listlike'
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```
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### 該当のソースコード
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'residential_percent_change_from_baseline': '住宅'})
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# 日本のデータのみ絞り込む (# データ数 = 6240件)
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print(df.info())
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df
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#print(df.info())
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grp = df.groupby('country_region_code').mean()
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df = grp.query('country_region_code == "JP"')
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import plotly_express as px
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df_melt = df.melt(id_vars='date', value_vars=["小売・娯楽", "食料品店・薬局", "公園", "乗換駅", "職場", "住宅"])
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fig = px.line(df_melt, x="date", y="value", color='variable',
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fig.show()
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```
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```
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###実行結果
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Data columns (total 13 columns):
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Column Non-Null Count Dtype
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--- ------ -------------- -----
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0 country_region_code 605422 non-null object
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1 country_region 606467 non-null object
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2 sub_region_1 588497 non-null object
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3 sub_region_2 350398 non-null object
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4 iso_3166_2_code 220137 non-null object
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5 census_fips_code 350532 non-null float64
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6 date 606467 non-null object
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7 小売・娯楽 464961 non-null float64
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8 食料品店・薬局 445097 non-null float64
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9 公園 276593 non-null float64
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10 乗換駅 322793 non-null float64
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11 職場 592165 non-null float64
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12 住宅 336291 non-null float64
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追記依頼の実行
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'residential_percent_change_from_baseline': '住宅'})
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# 日本のデータのみ絞り込む (# データ数 = 6240件)
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print(df.info())
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df = df.groupby("JP").mean()
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fig.show()
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```
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```
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###実行結果
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Data columns (total 13 columns):
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Column Non-Null Count Dtype
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--- ------ -------------- -----
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0 country_region_code 605422 non-null object
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1 country_region 606467 non-null object
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2 sub_region_1 588497 non-null object
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3 sub_region_2 350398 non-null object
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4 iso_3166_2_code 220137 non-null object
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5 census_fips_code 350532 non-null float64
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6 date 606467 non-null object
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7 小売・娯楽 464961 non-null float64
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8 食料品店・薬局 445097 non-null float64
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9 公園 276593 non-null float64
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10 乗換駅 322793 non-null float64
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11 職場 592165 non-null float64
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12 住宅 336291 non-null float64
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