Crypto data filtering

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, called data filtering, allows you to select specific data points based on your criteria. In this blog post, we’ll dive deeper into data filtering in the context of cryptocurrency. Let’s get into it!

What is data filtering?

Data filtering plays a crucial role in managing and analyzing information. It involves choosing specific pieces of information from a larger set of data, based on certain criteria. As a result, it helps to focus on relevant data, eliminate unimportant or incorrect data points, and enhance the overall quality and usefulness of the dataset.

By using filters, analysts and data scientists can concentrate on important subsets of data, which significantly improves their work efficiency. Moreover, data filtering has numerous applications. For instance, it can help examine results over a specific time, calculate metrics for certain groups, or exclude unusual or incorrect data that might skew results.

Data filtering can be either:

• Temporary – where analysts keep the full dataset but only use part of it for analysis
• Permanent – where they permanently delete or disregard irrelevant data from the very start

To decide which data to include in an analysis, data filtering employs specific rules. For example, in a sales dataset, a filter might only include transactions from the last quarter or exclude returns and refunds. Consequently, this approach improves the data quality and makes the subsequent analyses more accurate.

Data filtering serves as an essential technique in data processing and analysis, finding applications 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 involves refining and processing raw data to extract important information. Is it necessary? Absolutely! The cryptocurrency space overflows with data, including transaction data, market prices, trading volumes, social media sentiments (like 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 concentrate on crucial information. This includes removing outliers, duplicates, and anomalies that could distort the analysis.
• No biased data: Ensuring high-quality data 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 inform decision-making.

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:

• 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:

1<https://rest.coinapi.io/v1/symbols?filter_exchange_id=COINBASE>

• Filter by Asset: To get a list of symbols for Chainlink, use this endpoint:

1<https://rest.coinapi.io/v1/symbols?filter_asset_id=LINK>

• 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:

1<https://rest.coinapi.io/v1/ohlcv/BITSTAMP_SPOT_BTC_USD/history?period_id=1DAY&time_start=2022-01-01T00:00:00&time_end=2022-01-31T23:59:59>

• 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:

1<https://rest.coinapi.io/v1/trades/BITSTAMP_SPOT_BTC_USD/history?time_start=2022-01-01T00:00:00&time_end=2022-01-31T23:59:59>

• 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:

1<https://rest.coinapi.io/v1/symbols?filter_exchange_id=BINANCE>

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. Consequently, this helps you focus 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 proves 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. As a result, you can streamline the data flow and focus on the information that is most critical for your strategies.

What’s the main takeout?

Data filtering helps you quickly identify new trends in cryptocurrency markets, thus allowing you to make timely investment decisions and manage risks effectively. By focusing on important data and ignoring less important information, you can spot major market movements and patterns that might otherwise go unnoticed. Furthermore, using advanced data filtering techniques enables users to improve the accuracy of predictive models and develop more precise trading strategies.