Cryptocurrency historical price data library in Python. Data from https://coinmarketcap.com.

A python wrapper around the https://coinmarketcap.com API.

CoinMarketCap Python API Wrapper

a small python scraper to scrape historical data from the CoinMarketCap website and convert it to csv files . This is an initial step for a data mining process to develop a predictive model of cryptocurrencies prices.

Identify the software project, create business case, arrive at a problem statement. REQUIREMENT: Window XP, Internet, MS Office, etc. Problem Description: - 1. Introduction of AI and Machine Learning: - Artificial Intelligence applies machine learning, deep learning and other techniques to solve actual problems. Artificial intelligence (AI) brings the genuine human-to-machine interaction. Simply, Machine Learning is the algorithm that give computers the ability to learn from data and then make decisions and predictions, AI refers to idea where machines can execute tasks smartly. It is a faster process in learning the risk factors, and profitable opportunities. They have a feature of learning from their mistakes and experiences. When Machine learning is combined with Artificial Intelligence, it can be a large field to gather an immense amount of information and then rectify the errors and learn from further experiences, developing in a smarter, faster and accuracy handling technique. The main difference between Machine Learning and Artificial Intelligence is , If it is written in python then it is probably machine learning, If it is written in power point then it is artificial intelligence. As there are many existing projects that are implemented using AI and Machine Learning , And one of the project i.e., Bitcoin Price Prediction :- Bitcoin (₿ ) (founder - Satoshi Nakamoto , Ledger start: 3 January 2009 ) is a digital currency, a type of electronic money. It is decentralized advanced cash without a national bank or single chairman that can be sent from client to client on the shared Bitcoin arrange without middle people's requirement. Machine learning models can likely give us the insight we need to learn about the future of Cryptocurrency. It will not tell us the future but it might tell us the general trend and direction to expect the prices to move. These machine learning models predict the future of Bitcoin by coding them out in Python. Machine learning and AI-assisted trading have attracted growing interest for the past few years. this approach is to test the hypothesis that the inefficiency of the cryptocurrency market can be exploited to generate abnormal profits. the application of machine learning algorithms to the cryptocurrency market has been limited so far to the analysis of Bitcoin prices, using random forests , Bayesian neural network , long short-term memory neural network , and other algorithms. 2. Applications/Scope of AI and Machine Learning :- a) Sentiment Analysis :- It is the classification of subjective opinions or emotions (positive, negative, and neutral) within text data using natural language processing. b) It is Characterized as a use of computerized reasoning where accessible data is utilized through calculations to process or help the handling of factual information. BITCOIN PRICE PREDICTION USING AI AND MACHINE LEARNING: - The main aim of this is to find the actual Bitcoin price in US dollars can be predicted. The chance to make a model equipped for anticipating digital currencies fundamentally Bitcoin. # It works the prediction by taking the coinMarkup cap. # CoinMarketCap provides with historical data for Bitcoin price changes, keep a record of all the transactions by recording the amount of coins in circulation and the volume of coins traded in the last 24-hours. # Quandl is used to filter the dataset by using the MAT Lab properties. 3. Problem statement: - Some AI and Machine Learning problem statements are: - a) Data Privacy and Security: Once a company has dug up the data, privacy and security is eye-catching aspect that needs to be taken care of. b) Data Scarcity: The data is a very important aspect of AI, and labeled data is used to train machines to learn and make predictions. c) Data acquisition: In the process of machine learning, a large amount of data is used in the process of training and learning. d) High error susceptibility: In the process of artificial intelligence and machine learning, the high amount of data is used. Some problem statements of Bitcoin Price Prediction using AI and Machine Learning: - a) Experimental Phase Risk: It is less experimental than other counterparts. In addition, relative to traditional assets, its level can be assessed as high because this asset is not intended for conservative investors. b) Technology Risks: There is a technological risk to other cryptocurrencies in the form of the potential appearance of a more advanced cryptocurrency. Investors may simply not notice the moment when their virtual assets lose their real value. c) Price Variability: The variability of the value of cryptocurrency are the large volumes of exchange trading, the integration of Bitcoin with various companies, legislative initiatives of regulatory bodies and many other, sometimes disregarded phenomena. d) Consumer Protection: The property of the irreversibility of transactions in itself has little effect on the risks of investing in Bitcoin as an asset. e) Price Fluctuation Prediction: Since many investors care more about whether the sudden rise or fall is worth following. Bitcoin price often fluctuates by more than 10% (or even more than 30%) at some times. f) Lacks Government Regulation: Regulators in traditional financial markets are basically missing in the field of cryptocurrencies. For instance, fake news frequently affects the decisions of individual investors. g) It is difficult to use large interval data (e.g., day-level, and month-level data) . h) The change time of mining difficulties is much longer. Moreover, do not consider the news information since it is hard to determine the authenticity of a news or predict the occurrence of emergencies.

Python-based scraper for market cap, supply, exchange price, and exchange volume data from coinmarketcap.com

Python wrapper for coinmarketcap.com public API and private API. offer global market data,coin data,exchanges data and more https://github.com/shyuntech/coinmarketcap-api

:chart_with_upwards_trend: Python module for getting cryptocurrency data from Coinmarketcap :chart_with_downwards_trend:

python 3 scraper for coinmarketcap historical data

Simple python parser to display the results from coinmarketcap

This repository is used to pull cryptocurrency data from CoinMarketCap. Consolidated historical information is located within consolidated_coin_data.csv and can be refreshed by running the python script included.

A python script that fetches the price of any cryptocoin listed on coinmarketcap.com and sends a email when the coin has surpassed, or fallen below, a specific price.

Python 3+ API to retrieve, scrape and cache historical data from coinmarketcap.com

Simple Python script using both CoinMarketCap (ICOBench & CCN) and Discord API to alert user of current market.

Unofficial CoinMarketCap API and Python wrapper

A Python script which grabs information from both coinmarketcap.com and bitcointalk.org in order to get market information and announcement dates. Uses Python.

coinmarketcap.com crawler with python.

This program written in Python enables the user to analyze based on the market cap the new tokens that are upload everyday on CoinMarketCap .

Discord DCA Signal Bot is an open-source bot that provides automated Dollar Cost Averaging (DCA) and Take Profit signals for various cryptocurrencies in Discord servers. Built with Python and CoinMarketCap API.

Python script to generate XML data of cryptocurrencies from coinmarketcap.com API

Python calculator to convert any amount of dollars to an equivalent amount of crypto. Only works with the current top 10 cryptocurrencies on coinmarketcap.

coinmarketcap python scraper with selenium and bs4

A small program to get the price and other quantities of several cryptocurrencies from www.coinmarketcap.com. The information is stored in text files.

Python is the future of software development whereas Cryptocurrencies are the future of money. CoinMarketCap is the most up to date FREE API that you can access live cryptocurrency data today. In this project we have build five different projects using live cryptocurrency data from the web using python langauge. We will use the free CoinMarketCap crypto API.

Small python project for Raspberry Pi that fetches the prices from https://coinmarketcap.com/ and shows them on I2C 20x4 charachter LCD

Python script to check price for portfolio on CoinMarketCap.

Search for cryptocurrency prices using the CoinMarketCap API and Python

Python package for getting cryptocurrency prices and data from coinmarketcap

Python that monitors a set number of coins from coinmarketcap.com

A Python 3 portfolio for cryptocurrencies via data from www.coinmarketcap.com.