如何在将 dict 转换为 pandas DataFrame 时设置列标题（其中列名与 dict 键不匹配）？

Question

Using mongodb, I am outputting the unique field values and their number. Now I need to put this list in the ramp for further convenient work. But I don't quite understand how to do it because of the structure of the list.

unique_data = db.small_311.aggregate([ 
{'$group' : {'_id' : "$Complaint Type", 'uniqueCount' : {'$sum': 1}}}])

Part of the list

print(list(unique_data))
[{'_id': 'Posting Advertisement', 'uniqueCount': 5}, {'_id': 'APPLIANCE', 'uniqueCount': 445}, {'_id': 'Complaint', 'uniqueCount': 9},...]

I am trying to add to the dataframe

data_result = list(unique_data)
df = pd.DataFrame(data_result, columns =['Complaint Type', 'Value'])
df[:5]

But the result is an empty dataframe (it contains only the name of the fields, no data) Result dataframe

Answer 1

If you're just trying to rename your columns, you can use set_axis :

pd.DataFrame(d).set_axis(['A', 'B'], axis=1)

                       A    B
0  Posting Advertisement    5
1              APPLIANCE  445
2              Complaint    9

or just assign df.columns to a list directly.

---

To explain the output you're seeing, notice the columns argument does not match the keys in the records being passed to pd.DataFrame , so pandas doesn't select any columns. It doesn't understand you're trying to rename the columns.

Just passing your data as-is without any keyword arguments works:

pd.DataFrame(d)

                     _id  uniqueCount
0  Posting Advertisement            5
1              APPLIANCE          445
2              Complaint            9

If you want just the _id column, that's when you would use columns param.

pd.DataFrame(d, columns=['_id'])

                     _id
0  Posting Advertisement
1              APPLIANCE
2              Complaint

Passing a non-existent column will make it silently spit out nothing:

pd.DataFrame(d, columns=['blah'])

   blah
0   NaN
1   NaN
2   NaN