pandas.json_normalize question

[deanhystad]

Sounds like you know all you need to proceed. Time for you to start writing some code. Trial and error is important at the early stages of learning.

I wrote this to see what happens when I use pandas to load the json file I created earlier.

import pandas as pd

df = pd.read_json("data.json")
print(df)

Output:
    id        name                        fitness
0  1.0   Cole Volk  {'height': 130, 'weight': 60}
1  NaN    Mark Reg  {'height': 130, 'weight': 60}
2  2.0  Faye Raker  {'height': 130, 'weight': 60}

Notice that fitness is a dictionary, not columns. If I try to write the pandas dataframe to a csv format file:

import pandas as pd

df = pd.read_json("data.json")
df.to_csv("data.csv")

I get this in data.csv

Output:
,id,name,fitness
0,1.0,Cole Volk,"{'height': 130, 'weight': 60}"
1,,Mark Reg,"{'height': 130, 'weight': 60}"
2,2.0,Faye Raker,"{'height': 130, 'weight': 60}"

Not really a csv format file. That is why the dataframe had to be normalized.

import json
import pandas as pd


with open("data.json", "r") as file:
    data = json.load(file)
df = pd.json_normalize(data, max_level=1)
print(df)
df.to_csv("data.csv")

output

Output:
    id        name  fitness.height  fitness.weight
0  1.0   Cole Volk             130              60
1  NaN    Mark Reg             130              60
2  2.0  Faye Raker             130              60

data.csv

,id,name,fitness.height,fitness.weight
0,1.0,Cole Volk,130,60
1,,Mark Reg,130,60
2,2.0,Faye Raker,130,60

Notice in your original post that the call to pd.json_normalize() takes data, a list of dictionaries, not an existing dataframe as input. Read the json file to get the list of dictionaries. Use json_normalize(data) to create a dataframe that expands a dictionary into columns.

Your next post better have some code you wrote and error messages or sample input/output.