{"id":643,"date":"2022-09-28T05:47:53","date_gmt":"2022-09-28T05:47:53","guid":{"rendered":"https:\/\/eodhd.com\/financial-academy\/?p=643"},"modified":"2025-02-05T12:30:29","modified_gmt":"2025-02-05T12:30:29","slug":"create-trading-candlesticks-in-python","status":"publish","type":"post","link":"https:\/\/eodhd.com\/financial-academy\/stocks-data-analysis-examples\/create-trading-candlesticks-in-python","title":{"rendered":"Create Trading Candlesticks in Python"},"content":{"rendered":"\n

How to create custom trading candlesticks in Python and why?<\/p>\n\n\n\n

Important terminology and trading basics<\/strong>
Before I continue, you will need to have a grasp of some important terminology and trading basics.<\/p>\n\n\n\n

If you want to learn how to install the EODHD APIs Python Financial Official Library<\/a> and activate your API key, I recommend to start with exploring of our Documentation for it<\/a>.<\/p>\n\n\n\n

Let\u2019s start with a \u201cticker<\/strong>\u201d. What is it?<\/p>\n\n\n\n

A ticker represents any price change in a market. It is a constant stream of price changes. If you want to retrieve this live data, you will use a websocket. The Python library<\/a> I developed for EODHD APIs provides this functionality for you, and you can find a working example here\u2026<\/p>\n\n\n\n

eodhd\/example_websockets.py at main \u00b7 whittlem\/eodhd<\/strong>
\"Official
https:\/\/github.com\/EodHistoricalData\/EODHD-APIs-Python-Financial-Library\/blob\/main\/example_websockets.py<\/a><\/p>\n\n\n\n

The ticker in isolation does not help us determine when to buy or sell in a market. In order to do this we need to look at the historical data for a market. Now you can image trying to analyse hundreds of thousands or even millions of price changes without any time reference won\u2019t help you. This is where granularity\/resolution\/interval comes into play.<\/p>\n\n\n\n

What is \u201cgranularity\/resolution\/interval<\/strong>\u201d in a market?<\/p>\n\n\n\n

These words get used interchangeably depending on the exchange, but really they are the same thing. An \u201cinterval<\/strong>\u201d, \u201cgranularity<\/strong>\u201d or \u201cresolution<\/strong>\u201d is a sort of grouping of price information. An \u201cinterval<\/strong>\u201d of 1 hour means that all price data for each hour will be consolidated. Each interval of data (in this case an hour) is represented as a \u201ccandlestick<\/strong>\u201d.<\/p>\n\n\n\n

What is a \u201ccandlestick<\/strong>\u201d in trading?<\/p>\n\n\n\n

A candlestick represents one interval, in our case, an hour. It is made up of the Open<\/strong>, High<\/strong>, Low<\/strong>, and Close<\/strong>. The Open<\/strong> is the first price of the hour, the High<\/strong> is the highest price of the hour, the Low<\/strong> is the lowest price of the hour, and the Close<\/strong> is the last price of the hour. In algorithmic trading this is often known as \u201cOHLC<\/strong>\u201d. In fact if you search for \u201cOHLC<\/strong>\u201d in your search engine you will find loads of information about it. You may also see \u201cOHLCV<\/strong>\u201d. The V is for Volume,<\/strong> and the sum of the volume of trades done within the hour.<\/p>\n\n\n\n

On trading graphs you will see a series of candlesticks which look like this.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

What determines if a candlestick is green or red depends on if the candlestick closes closes higher or lower than the opening price.<\/p>\n\n\n\n

<\/p>\n\n\n\n

Register & Get Data<\/span><\/a><\/p>\n\n\n\n

Why would you want to create your own trading candlesticks in Python?<\/h2>\n\n\n\n

Not all exchanges and data providers support all intervals. If you compare EODHD APIs, TradingView, Coinbase, Binance, IG, etc. you will see there is a vast range of options.<\/p>\n\n\n\n

You may also want to construct your own trading candlesticks in Python from a websocket price ticker feed. If you have a constant stream of ticker information coming in, what you would do is capture the first price of the interval (that would be your Open, High, and Low). When subsequent prices come in you will check if the price is higher or lower than the current High or Low. If there is a difference, then set the appropriate value. When you reach the end of the interval you will set the closing price of the interval in Close. If you are capturing the volume data, you will just sum up the total volume and assign it to Volume. At the end of the interval you should have a candlestick with the opening price, highest price of the interval, lowest price of the interval, and the closing price.<\/p>\n\n\n\n

If you are interested in how I did this, you can check the code in my PyCryptoBot<\/a> project.<\/p>\n\n\n\n

Look at the WebSocketClient class.<\/p>\n\n\n\n

Register & Get Data<\/span><\/a><\/p>\n\n\n\n

Creating our first custom trading candlesticks in Python<\/h2>\n\n\n\n

There are a few ways this can be done, and I\u2019ll show you two of them. Most exchanges and data providers only provide a maximum of 1 hour or 6 hour intraday intervals. What if we wanted \u201cweekly<\/strong>\u201d trading candlesticks in Python? This is a really powerful interval to plot a long term trend, but not many provide it.<\/p>\n\n\n\n

I\u2019m going to use a Jupyter notebook in Google Colab<\/a>. It\u2019s free and easy to use if you want to follow along. I\u2019m also going to use the EODHD APIs end-of-day demo key to demonstrate this.<\/p>\n\n\n\n

The first step is we need to import our libraries.<\/p>\n\n\n\n

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import json\nimport requests\nimport pandas as pd\nfrom datetime import datetime, timedelta<\/code><\/pre>\n\n                <\/div>\n                
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