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Market Data API

Crypto data filtering

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It’s 9:00 AM. You make a morning coffee and sit at your desk ready to trade crypto. When you turn on your computer, you see a lot of market data and crypto news. Instead of analyzing every single data point and reading all crypto news websites (which would be impossible), you can save time by setting up filters. These filters help you focus on the most important information like major price changes, high trading volumes, significant news events, or just the one altcoin you’re interested in. This process is called data filtering, allowing you to select specific data points based on your own criteria. In this blog post, we’ll talk more about data filtering in the context of cryptocurrency. Let’s get into it!

What is data filtering?

Filtering of data is one of the main parts of managing and analyzing information. It’s about choosing specific pieces of information from a larger set of data, based on certain criteria. It helps to focus on relevant data, get rid of unimportant or wrong data points, and improve the overall quality and usefulness of the dataset.

By using filters, analysts and data scientists can concentrate on important subsets of data, which makes their work more efficient. Data filtering can be used in many ways. For example, it can be used to look at results over a specific time, calculate metrics for certain groups, or exclude unusual or incorrect data that could affect results.

Data filtering can be either:

  • Temporary – the full dataset is kept but only part of it is used for analysis
  • Permanent – where irrelevant data is permanently deleted or not considered from the very start

Data filtering uses specific rules to decide which data to include in an analysis. For example, in a sales dataset, a filter might only include transactions from the last quarter or exclude returns and refunds. This approach improves the quality of the data and makes the following analyses more accurate.

Data filtering is an essential technique in data processing and analysis, used in business intelligence, data science, machine learning, finance, and cryptocurrency. By refining raw data into smaller and meaningful sets, filtering supports better data examination, model training, and decision-making processes.

What’s the goal of crypto data filtering?

Filtering data in cryptocurrency means refining and processing raw data to extract important information. Is it necessary? We believe so! There is a lot of data in the cryptocurrency space including transaction data, market prices, trading volumes, social media sentiments (the community on X arguing over most strategies), and blockchain analytics.

Main purposes of data filtering in cryptocurrency?

  • Focus on important insights: Filtering out irrelevant or incorrect data to focus on important information. It includes removing outliers, duplicates, and anomalies that could affect the analysis.
  • No biased data: Ensuring that the data is of good quality by addressing missing values, correcting errors, and standardizing data formats.
  • Easier to find interesting info: Identifying and isolating important patterns, trends, and signals from the data that can be used to make decisions.

How is Market Data API filtering crypto data?

Our Market Data API offers a variety of options for filtering data to ensure you only get the information you need:

  1. Symbol Filtering

    • You can narrow down your data requests to specific symbols, allowing you to retrieve data for only the assets or trading pairs that interest you. This means you won’t be overwhelmed by unnecessary data.
    • To filter symbols for a specific exchange or asset, you can use the filter_exchange_id or filter_asset_id parameters. Here’s how to do it:
      • Filter by Exchange: To get a list of symbols for the Coinbase exchange, use the following endpoint:
      • Filter by Asset: To get a list of symbols for Chainlink, use this endpoint:
  2. Time Range Filtering

    • If you need historical data from a particular period, you can specify a time range for your query. This is especially useful for analyzing past market trends or conducting backtesting on specific time frames.
    • To filter data by a specific time range, use the time_start and time_end parameters. For example:
      • OHLCV Data for Bitcoin: To retrieve OHLCV data for Bitcoin (BTC) from January 1, 2022, to January 31, 2022:
  3. Data Type Filtering

    • The API provides the flexibility to filter by different types of market data. Whether you’re interested in trades, quotes, order books, or OHLCV (Open, High, Low, Close, Volume) data, you can tailor your request to match your needs.
    • To filter data by type, specify the data type in the endpoint. For example:
      • Trade Data: To get trade data for Bitcoin on the Bitstamp exchange from January 1, 2022, to January 31, 2022:
  4. Exchange Filtering

    • Focus your data retrieval on specific exchanges. This option is ideal if you’re only interested in data from certain exchanges, making your analysis more relevant and precise.
    • To filter data by a specific exchange, use the filter_exchange_id parameter. For example:
      • Filter by Exchange: To get a list of symbols for the Binance exchange:

Filtering real-time crypto data

Most people when thinking about data filtering apply it to historical data only, but it is possible to filter real-time data using the CoinAPI’s Market Data API.

When using the WebSocket API protocol for real-time data streaming, you can apply various filters to receive only the specific data you need.

Here are some ways to filter real-time data:

  • Symbol Filtering

    You can subscribe to specific symbols to receive real-time updates only for those assets or trading pairs. This helps in focusing on the most relevant data for your trading or analysis purposes.

  • Exchange Filtering

    You can filter the data to receive updates from specific exchanges. This is useful if you are interested in tracking data from particular exchanges where you actively trade or analyze market conditions.

  • Data Type Filtering

    You can choose to receive specific types of real-time data, such as trades, quotes, or order book updates. This allows you to streamline the data flow and focus on the information that is most critical for your strategies.

What’s the main takeout?

Data filtering helps to quickly find new trends in cryptocurrency markets, allowing you to make timely investment decisions and manage risks effectively. By focusing on important data and ignoring the less important information, you could spot major market movements and patterns that might otherwise be missed. Using advanced data filtering techniques, allows users to improve the accuracy of predictive models and develop more precise trading strategies.

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