Question

我正在尝试使用唯一的ID为仅存在于一个数据集中的客户端合并两个数据集。我已经为每个全名分配了唯一的ID作为字典，但是每个人都是唯一的，即使他们的名字相同。我需要将每个唯一的ID迭代地分配给该人姓名的每个实例。

字典示例：

{'Corey Davis': {'names_id':[1472]}, 'Jose Hernandez': {'names_id': [3464,15202,82567,98472]}, ...}

我已经尝试过使用.map（）函数以及

referrals['names_id'] = referrals['full_name'].copy()
for key, val in m.items():
    referrals.loc[referrals.names_id == key, 'names_id'] = val

但是，当然，它只会分配遇到的最后一个值98472。

我希望有以下类似的东西

full_name         names_id \
Corey Davis       1472
Jose Hernandez    3464
Jose Hernandez    15202
Jose Hernandez    82657
Jose Hernandez    98472

但我知道

full_name         names_id \
Corey Davis       1472
Jose Hernandez    98472
Jose Hernandez    98472
Jose Hernandez    98472
Jose Hernandez    98472

Answer 1

我个人想做的是：

inputs = [{'full_name':'test', 'names_id':[1]}, {'full_name':'test2', 'names_id':[2,3,4]}]
# Create list of dictionaries for each 'entry'
entries = []
for input in inputs:
    for name_id in input['names_id']:
        entries.append({'full_name': input['full_name'], 'names_id': name_id})

# Now you have a list of dicts - each being one line of your table
# entries is now
# [{'full_name': 'test', 'names_id': 1},
# {'full_name': 'test2', 'names_id': 2},
# {'full_name': 'test2', 'names_id': 3},
# {'full_name': 'test2', 'names_id': 4}]

# I like pandas and use it for its dataframes, you can create a dataframe from list of dicts

import pandas as pd
final_dataframe = pd.DataFrame(entries)

我可以使用词典将多个唯一ID分配给重复组吗？

1 个答案: