How to save stock data to csv file using python

Borrowing from How do I write a Python dictionary to a csv file?

You have a nested dict structure. Maybe the following will help:

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.

These are the contents of mycsvfile.csv:

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. It'll probably give you more ideas.

UPDATE AS PER OP'S COMMENT:

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:

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:

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