Pandas : 如何使用 .agg()

Question

我有一个数据框，其中包含客户对他们去过的餐厅的评分以及其他一些属性。

我想做的是计算去年的平均星级和去年的平均星级之间的差值餐厅元年


data = {'rating_id': ['1', '2','3','4','5','6','7'],
        'user_id': ['56', '13','56','99','99','13','12'],
        'restaurant_id':  ['xxx', 'xxx','yyy','yyy','xxx','zzz','zzz'],
        'star_rating': ['2.3', '3.7','1.2','5.0','1.0','3.2','1.0'],
        'rating_year': ['2012','2012','2020','2001','2020','2015','2000'],
        'first_year': ['2012', '2012','2001','2001','2012','2000','2000'],
        'last_year': ['2020', '2020','2020','2020','2020','2015','2015'],
        }

df = pd.DataFrame (data, columns = ['rating_id','user_id','restaurant_id','star_rating','rating_year','first_year','last_year'])

df.head()

df['star_rating'] = df['star_rating'].astype(float)

# calculate the average of the stars of the first year 

ratings_mean_firstYear= df.groupby(['restaurant_id','first_year']).agg({'star_rating':[np.mean]})
ratings_mean_firstYear.columns = ['avg_firstYear']
ratings_mean_firstYear.reset_index()

# calculate the average of the stars of the last year 

ratings_mean_lastYear= df.groupby(['restaurant_id','last_year']).agg({'star_rating':[np.mean]})
ratings_mean_lastYear.columns = ['avg_lastYear']
ratings_mean_lastYear.reset_index()

# merge the means into a single table

ratings_average = ratings_mean_firstYear.merge(
    ratings_mean_lastYear.groupby('restaurant_id')['avg_lastYear'].max()
    , on='restaurant_id'
)

ratings_average.head(20)

我的问题是第一年和最后几年的平均值完全相同，这毫无意义，我真的不知道我在这里的思考过程中做错了什么..我怀疑发生了什么事使用 .agg 因为这是我第一次使用 pandas lib.

有什么建议吗？

Answer 1

您的数据以这样的方式提供，即每 user/restaurant 对具有单一评级，并且您在第一年和去年的汇总中都使用它 - 因此这两年自然是相等的。我首先使用 rating_year == first_year 条件过滤数据，然后应用 groupby 和 agg。然后对去年重复相同的操作，然后合并 2 个结果。在您的示例中，没有一条评论的数据与任何餐厅的第一年或最后一年相匹配。因此，要显示适当的示例将需要更多数据。我假设您在较大的数据框中拥有它。 –

这是一个示例，我添加了更多行并更改了年份以获得更多匹配项：

data = {'rating_id': ['1', '2','3','4','5','6','7','8','9'],
        'user_id': ['56', '56','56','56', '99','99','99','99','99'],
        'restaurant_id':  ['xxx', 'xxx','yyy','yyy','xxx', 'xxx','yyy','yyy','xxx'],
        'star_rating': ['2.3', '3.7','1.2','5.0','1.0','3.2','4.0','2.5','3.0'],
        'rating_year': ['2012', '2020','2001','2020', '2012', '2020','2001','2020','2019'],
        'first_year': ['2012', '2012','2001','2001','2012', '2012','2001','2001','2012'],
        'last_year': ['2020', '2020','2020','2020','2020','2020','2020','2020','2020'],
        }

df = pd.DataFrame (data, columns = ['rating_id','user_id','restaurant_id','star_rating','rating_year','first_year','last_year'])
df['star_rating'] = df['star_rating'].astype(float)

ratings_mean_firstYear = df[df.rating_year == df.first_year].groupby('restaurant_id').agg({'star_rating':'mean'})
ratings_mean_firstYear.columns = ['avg_firstYear']
ratings_mean_lastYear= df[df.rating_year == df.last_year].groupby('restaurant_id').agg({'star_rating':'mean'})
ratings_mean_lastYear.columns = ['avg_lastYear']

结果：

ratings_mean_firstYear.merge(ratings_mean_lastYear, left_index=True, right_index=True)

               avg_firstYear  avg_lastYear
restaurant_id                             
xxx                     1.65          3.45
yyy                     2.60          3.75

Pandas : 如何使用 .agg()

Pandas : How to use .agg()

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