如何生成从 JSON 文件获取数据的图表

Question

I have a json file in which I have different data, I need to generate a graph whose legend is "Dates" and whose data is all the viewers of each user. I've been trying to do it all morning, but I have no idea, can someone help me?

{
    "Avg": 49,
    "Max": 70,
    "Dates": ["01/01/2019 01:05", "01/01/2019 01:10", "01/01/2019 01:15", "01/01/2019 01:20", "01/01/2019 01:25", "01/01/2019 01:30", "01/01/2019 01:35"],
    "Viewers": [
        {
            "Name": "User1",
            "Viewers": [1,2,3,4,5,6,7]
        },
        {
            "Name": "User2",
            "Viewers": [2,3,4,5,6,7,8]
        },
        {
            "Name": "User3",
            "Viewers": [3,4,5,6,7,8,9]
        },
        {
            "Name": "User4",
            "Viewers": [4,5,6,7,8,9,10]
        },
        {
            "Name": "user5",
            "Viewers": [5,6,7,8,9,10,11]
        },
        {
            "Name": "User6",
            "Viewers": [6,7,8,9,10,11,12]
        },
        {
            "Name": "User7",
            "Viewers": [7,8,9,10,11,12,13]
        },
        {
            "Name": "Total",
            "Viewers": [28, 35, 42, 49, 56, 63, 70]
        }
    ]
}

Answer 1

Assume that you have put the json data in a faile named input.json

import json
import matplotlib.pyplot as plt

with open('input.json') as fp:
    json_data = json.load(fp)

for v in json_data['Viewers']:
    plt.plot(json_data['Dates'], v['Viewers'], label=v['Name'])
    
plt.legend()
plt.xticks(rotation = 20)

# to save as png, it should be done before plt.show()
plt.savefig('graph.png')
plt.show()

And here is the result

Answer 2

Assuming original question is exact, meaning plot needs to show 'Dates' in Legend, and data should not include Total , only data for each user:

• understanding the data:

    import pandas as pd 
    import plotly.express as px
    data = [...]
    dates = data['Dates']
    users = [x['Name'] for x in data['Viewers']] 
    viewers = [x['Viewers'] for x in data['Viewers']][:-1] 
    data_list = [(dates[index], users[index2], y) for index, x in enumerate(viewers) for index2, y in enumerate(x)] 
    df = pd.DataFrame(data_list, columns =['Date', 'User', 'Viewers']) 
    

• plotting it:

    fig = px.bar(df, y='Viewers', x = 'User', color = 'Date', barmode="group") 
    fig.show()
    

• result: Plot with 'Dates' as legend

That being said, a time series is usually intelligible if timeline is on x axis. However, given the requirements, I believe this is the correct answer.