python - Pandas 数据帧到 JSON 格式的操作

Question

我有像这样的 pandas DataFrame

User  Category    Rating
1     [1,2,3]     [5,1,3]
2     [3,2,1]     [3,1,1]
3     [1,3,1]     [2,1,4]

我想编写一个端点，它接受用户并返回特定用户的类别和评级列表。

www.endpoint.com/user/1

应该返回

[{类别:1，评级:5}，{类别:2，评级:1}，{类别:3，评级:3}]

在 Pandas 中是否有一种简单的方法可以做到这一点？

Answer 1

我会使用the following generic function which explodes lists in columns into rows :

def explode(df, lst_cols, fill_value=''):
    # make sure `lst_cols` is a list
    if lst_cols and not isinstance(lst_cols, list):
        lst_cols = [lst_cols]
    # all columns except `lst_cols`
    idx_cols = df.columns.difference(lst_cols)

    # calculate lengths of lists
    lens = df[lst_cols[0]].str.len()

    if (lens > 0).all():
        # ALL lists in cells aren't empty
        return pd.DataFrame({
            col:np.repeat(df[col].values, df[lst_cols[0]].str.len())
            for col in idx_cols
        }).assign(**{col:np.concatenate(df[col].values) for col in lst_cols}) \
          .loc[:, df.columns]
    else:
        # at least one list in cells is empty
        return pd.DataFrame({
            col:np.repeat(df[col].values, df[lst_cols[0]].str.len())
            for col in idx_cols
        }).assign(**{col:np.concatenate(df[col].values) for col in lst_cols}) \
          .append(df.loc[lens==0, idx_cols]).fillna(fill_value) \
          .loc[:, df.columns]

演示:

In [88]: df
Out[88]:
   User   Category     Rating
0     1  [1, 2, 3]  [5, 1, 3]
1     2  [3, 2, 1]  [3, 1, 1]
2     3  [1, 3, 1]  [2, 1, 4]

In [89]: cols = ['Category','Rating']

In [90]: x = explode(df, cols)

In [91]: x
Out[91]:
   User Category Rating
0     1        1      5
1     1        2      1
2     1        3      3
3     2        3      3
4     2        2      1
5     2        1      1
6     3        1      2
7     3        3      1
8     3        1      4

现在我们可以轻松满足您的需求:

In [92]: x.loc[x.User == 1, cols].to_dict('r')
Out[92]:
[{'Category': '1', 'Rating': '5'},
 {'Category': '2', 'Rating': '1'},
 {'Category': '3', 'Rating': '3'}]