Question

如何将字典溢出并将信息添加到数据框中的行？值是包含字典的列表，我想将'key'移动到dataframe中的'column'，将'value'移动到dataframe中的值。例如，原始数据帧是

   Dataframe df:
    id    options
0    0     [{'a':1 ,'b':2},{'a':3 ,'b':4}]
1    1     [{'a':5 ,'b':6},{'a':7 ,'b':8}]
2    2     [{'a':9 ,'b':10},{'a':11,'b':12}]

我想将结构改为如下

     id    a    b
0    0     1    2
1    0     3    4
2    1     5    6
3    1     7    8
4    2     9    10    
5    2     11   12

Answer 1

试试这个：

lst_cols = ['options']

pd.DataFrame({
    col:np.repeat(df[col].values, df[lst_cols[0]].str.len())
    for col in df.columns.drop(['options'])
}).join(pd.DataFrame.from_records(np.concatenate(df.options.values)))

输出：

Out[45]:
   id   a   b
0   0   1   2
1   0   3   4
2   1   5   6
3   1   7   8
4   2   9  10
5   2  11  12

Answer 2

# Produce Example DataFrame
options = pd.Series([[{'a':1 ,'b':2},{'a':3 ,'b':4}], 
                     [{'a':5 ,'b':6},{'a':7 ,'b':8}],
                     [{'a':9 ,'b':10},{'a':11,'b':12}]
                     ])

df = pd.DataFrame({'id': [0,1,2], 'options': options})

# Initialize df to hold results
final_df = pd.DataFrame()

# Iterate through df. We will use 'row' but not 'index'
for index, row in df.iterrows():

    # row is a series with two elements. first is id, second is list of dicts
    list_of_dicts = row['options']
    row_as_df     = pd.DataFrame(list_of_dicts)  

    # Add back id column and append as new rows in final df of results
    row_as_df['id'] = row['id']            
    final_df        = pd.concat([final_df, row_as_df], axis=0)


final_df.reset_index(drop=True)

输出

    a   b  id
0   1   2   0
1   3   4   0
2   5   6   1
3   7   8   1
4   9  10   2
5  11  12   2

python：如何将字典溢出并将信息添加到数据帧中的行？

2 个答案: