[英]Output pandas dataframe to json in a particular format
我的数据框是
fname lname city state code
Alice Lee Athens Alabama PXY
Nor Xi Mesa Arizona ABC
json的输出应该是
{
"Employees":{
"Alice Lee":{
"code":"PXY",
"Address":"Athens, Alabama"
},
"Nor Xi":{
"code":"ABC",
"Address":"Mesa, Arizona"
}
}
}
df.to_json()
没有给 json 提供层次结构。 你能建议我错过什么吗? 有没有办法在 Pandas 中编写 json 时组合列并给它们一个“键名”?
谢谢你。
尝试:
names = df[["fname", "lname"]].apply(" ".join, axis=1)
addresses = df[["city", "state"]].apply(", ".join, axis=1)
codes = df["code"]
out = {"Employees": {}}
for n, a, c in zip(names, addresses, codes):
out["Employees"][n] = {"code": c, "Address": a}
print(out)
印刷:
{
"Employees": {
"Alice Lee": {"code": "PXY", "Address": "Athens, Alabama"},
"Nor Xi": {"code": "ABC", "Address": "Mesa, Arizona"},
}
}
我们可以填充一个新的数据框,其中的列是"code"
和"Address"
,索引是"full_name"
,其中后两个是从数据框的列中生成的字符串添加:
new_df = pd.DataFrame({"code": df["code"],
"Address": df["city"] + ", " + df["state"]})
new_df.index = df["fname"] + " " + df["lname"]
这使
>>> new_df
code Address
Alice Lee PXY Athens, Alabama
Nor Xi ABC Mesa, Arizona
我们现在可以使用orient="index"
调用to_dict
:
>>> d = new_df.to_dict(orient="index")
>>> d
{"Alice Lee": {"code": "PXY", "Address": "Athens, Alabama"},
"Nor Xi": {"code": "ABC", "Address": "Mesa, Arizona"}}
为了匹配您的输出,我们用字典包装d
:
>>> {"Employee": d}
{
"Employee":{
"Alice Lee":{
"code":"PXY",
"Address":"Athens, Alabama"
},
"Nor Xi":{
"code":"ABC",
"Address":"Mesa, Arizona"
}
}
}
json = json.loads(df.to_json(orient='records'))
employees = {}
employees['Employees'] = [{obj['fname']+' '+obj['lname']:{'code':obj['code'], 'Address':obj['city']+', '+obj['state']}} for obj in json]
这输出 -
{
'Employees': [
{
'Alice Lee': {
'code': 'PXY',
'Address': 'Athens, Alabama'
}
},
{
'Nor Xi': {
'code': 'ABC',
'Address': 'Mesa, Arizona'
}
}
]
}
你可以使用 df.iterrows() 解决这个问题
employee_dict = {}
for row in df.iterrows():
# row[0] is the index number, row[1] is the data respective to that index
row_data = row[1]
employee_name = row_data.fname + ' ' + row_data.lname
employee_dict[employee_name] = {'code': row_data.code, 'Address':
row_data.city + ', ' + row_data.state}
json_data = {'Employees': employee_dict}
结果:
{'Employees': {'Alice Lee': {'code': 'PXY', 'Address': 'Athens, Alabama'},
'Nor Xi': {'code': 'ABC', 'Address': 'Mesa, Arizona'}}}
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