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使用 Pandas 将 csv 转换为 json 以在 highcharts highstock

问题是在类似于以下仅显示一个系列的 highcharts highstock 图表中显示两个系列,用于调整高点和调整低点:

链接到类似的 Highstock 问题和 JSFiddle:


https://forum.highcharts.com/viewtopic.php?f=12&t=40964&p=142595&hilit=multiple+series#p142595


https://jsfiddle.net/BlackLabel/xqgv2b4k/


下面是我用来生成上图的工作文件。


样本.csv(输入)


DATE,ADJ_HIGH,ADJ_LOW

2018-04-27,164.33,160.630

2018-04-30,167.26,161.840

2018-05-01,169.20,165.270

2018-05-02,177.75,173.800

2018-05-03,177.50,174.441

csv_to_json_testing.py


import numpy as np

import pandas as pd


input_file = 'sample.csv'


df = pd.read_csv(input_file, usecols=[0,1,2], parse_dates=['DATE'], date_parser = pd.to_datetime) #  keep_default_na = False


with open('overflow.txt', 'w') as f:

    df['DATE'] = df['DATE'].values.astype(np.int64) // 10 ** 6

    print(file=f)

    print('DATE, ADJ_HIGH (json)', file=f)

    print(file=f)

    print(df[['DATE','ADJ_HIGH']].tail(5).to_json(orient='values'), file=f)

    print(file=f)

    print('DATE, ADJ_LOW (json)', file=f)

    print(file=f)

    print(df[['DATE','ADJ_LOW']].tail(5).to_json(orient='values'), file=f)

    print(file=f)

    print('DATE, ADJ_HIGH, ADJ_LOW (json)', file=f)

    print(file=f)

    print(df[['DATE','ADJ_HIGH','ADJ_LOW']].tail(5).to_json(orient='values'), file=f)

溢出.txt(输出)


DATE, ADJ_HIGH (json)


[[1524787200000,164.33],[1525046400000,167.26],[1525132800000,169.2],[1525219200000,177.75],[1525305600000,177.5]]


DATE, ADJ_LOW (json)


[[1524787200000,160.63],[1525046400000,161.84],[1525132800000,165.27],[1525219200000,173.8],[1525305600000,174.441]]


DATE, ADJ_HIGH, ADJ_LOW (json)


[[1524787200000,164.33,160.63],[1525046400000,167.26,161.84],[1525132800000,169.2,165.27],[1525219200000,177.75,173.8],[1525305600000,177.5,174.441]]

sample.json (DATE, ADJ_HIGH)



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