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如何使用python将股票数据保存到csv文件

[英]How to save stock data to csv file using python

I am trying to save the stock data I downloaded from a API using python. 我正在尝试保存使用python从API下载的股票数据。 But I have no idea about how to do this. 但是我不知道该怎么做。

The data is printed out as below: 数据打印如下:

>>> 
{'20140311': {'1030': {'total_price': 9421626, 'end': 6.76, 'high': 6.85, 'start': 6.78, 'low': 6.67, 'volumn': 1396431}, '1130': {'total_price': 5042807, 'end': 6.86, 'high': 6.91, 'start': 6.76, 'low': 6.76, 'volumn': 735220}, '1400': {'total_price': 5410292, 'end': 6.79, 'high': 6.9, 'start': 6.88, 'low': 6.76, 'volumn': 792890}, '1500': {'total_price': 6470290, 'end': 6.83, 'high': 6.85, 'start': 6.79, 'low': 6.74, 'volumn': 954111}},....

My last several lines of the code is: 我的最后几行代码是:

def main():
    g = getStock60MIN('000030', 'sz')
    print g

if __name__ == "__main__":
    main()

Borrowing from How do I write a Python dictionary to a csv file? 如何将Python字典写入csv文件中借用

You have a nested dict structure. 您具有嵌套的dict结构。 Maybe the following will help: 也许以下方法会有所帮助:

import csv

my_dict = {
  '20140311': {
    '1030': {
      'total_price': 9421626, 'end': 6.76, 'high': 6.85, 'start': 6.78, 'low': 6.67, 'volumn': 1396431
    },
    '1130': {
      'total_price': 5042807, 'end': 6.86, 'high': 6.91, 'start': 6.76, 'low': 6.76, 'volumn': 735220
    },
    '1400': {
      'total_price': 5410292, 'end': 6.79, 'high': 6.9, 'start': 6.88, 'low': 6.76, 'volumn': 792890
    }, 
    '1500': {
      'total_price': 6470290, 'end': 6.83, 'high': 6.85, 'start': 6.79, 'low': 6.74, 'volumn': 954111
    }
  }
}

def initialize_keys():
  for dict1 in my_dict.itervalues():
    for dict2 in dict1.itervalues():
      return dict2.keys()

with open('mycsvfile.csv', 'wb') as f:
  w = csv.DictWriter(f, initialize_keys())
  w.writeheader()
  for dict1 in my_dict.itervalues():
    for dict2 in dict1.itervalues():
      w.writerow(dict2)

I don't know what do you want to do with your secondary dictionary keys, though (the 1030 , 1130 , 1400 and 1500 ) My method disregards them. 我不知道你想用辅助字典键做什么,但(在1030113014001500 ),我的方法忽略它们。

These are the contents of mycsvfile.csv : 这些是mycsvfile.csv的内容:

total_price,end,high,start,low,volumn
9421626,6.76,6.85,6.78,6.67,1396431
5042807,6.86,6.91,6.76,6.76,735220
5410292,6.79,6.9,6.88,6.76,792890
6470290,6.83,6.85,6.79,6.74,954111

Take a look to the csv module in Python. 看一下Python中的csv模块。 It'll probably give you more ideas. 它可能会给您更多的想法。


UPDATE AS PER OP'S COMMENT: 根据OP的评论进行更新:

Since the keys of the first dictionary are dates and the keys of the second dictionary are times, a datetime.datetime instance can be instanciated and then written in the csv file: 由于第一个字典的键是日期,而第二个字典的键是时间,因此可以实例化datetime.datetime实例,然后将其写入csv文件中:

import csv
import datetime

my_dict = {
  '20140311': {
    '1030': {
      'total_price': 9421626, 'end': 6.76, 'high': 6.85, 'start': 6.78, 'low': 6.67, 'volumn': 1396431
    },
    '1130': {
      'total_price': 5042807, 'end': 6.86, 'high': 6.91, 'start': 6.76, 'low': 6.76, 'volumn': 735220
    },
    '1400': {
      'total_price': 5410292, 'end': 6.79, 'high': 6.9, 'start': 6.88, 'low': 6.76, 'volumn': 792890
    }, 
    '1500': {
      'total_price': 6470290, 'end': 6.83, 'high': 6.85, 'start': 6.79, 'low': 6.74, 'volumn': 954111
    }
  }
}

def initialize_keys():
  for dict1 in my_dict.itervalues():
    for dict2 in dict1.itervalues():
      return dict2.keys()

with open('mycsvfile.csv', 'wb') as f:
  w = csv.DictWriter(f, ['datetime'] + initialize_keys())
  w.writeheader()
  for datestr, dict1 in my_dict.iteritems():
    for timestr, dict2 in dict1.iteritems():
      whole_row = {}
      whole_row['datetime'] = datetime.datetime\
                .strptime(datestr + timestr, '%Y%m%d%H%M')\
                .strftime('%Y/%m/%d %H:%M')
      whole_row.update(dict2)
      w.writerow(whole_row)

This produces the following output: 这将产生以下输出:

datetime,total_price,end,high,start,low,volumn
2014/03/11 10:30,9421626,6.76,6.85,6.78,6.67,1396431
2014/03/11 11:30,5042807,6.86,6.91,6.76,6.76,735220
2014/03/11 14:00,5410292,6.79,6.9,6.88,6.76,792890
2014/03/11 15:00,6470290,6.83,6.85,6.79,6.74,954111

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