investpy.crypto

investpy.crypto.get_crypto_historical_data(crypto, from_date, to_date, as_json=False, order='ascending', interval='Daily')

This function retrieves historical data from the introduced crypto from Investing.com. So on, the historical data of the introduced crypto will be retrieved and returned as a pandas.DataFrame if the parameters are valid and the request to Investing.com succeeds. Note that additionally some optional parameters can be specified: as_json and order, which let the user decide if the data is going to be returned as a json or not, and if the historical data is going to be ordered ascending or descending (where the index is the date), respectively.

Parameters

  • crypto (str) – name of the crypto currency to retrieve data from.

  • from_date (str) – date formatted as dd/mm/yyyy, since when data is going to be retrieved.

  • to_date (str) – date formatted as dd/mm/yyyy, until when data is going to be retrieved.

  • as_json (bool, optional) – to determine the format of the output data, either a pandas.DataFrame if False and a json if True.

  • order (str, optional) – to define the order of the retrieved data which can either be ascending or descending.

  • interval (str, optional) – value to define the historical data interval to retrieve, by default Daily, but it can also be Weekly or Monthly.

Returns

The function can return either a pandas.DataFrame or a json object, containing the retrieved historical data of the specified crypto currency. So on, the resulting dataframe contains the open, high, low, close and volume values for the selected crypto on market days and the currency in which those values are presented.

The returned data is case we use default arguments will look like:

Date || Open | High | Low | Close | Volume | Currency
-----||------|------|-----|-------|--------|----------
xxxx || xxxx | xxxx | xxx | xxxxx | xxxxxx | xxxxxxxx

but if we define as_json=True, then the output will be:

{
    name: name,
    historical: [
        {
            date: 'dd/mm/yyyy',
            open: x,
            high: x,
            low: x,
            close: x,
            volume: x,
            currency: x
        },
        ...
    ]
}

Return type

pandas.DataFrame or json

Raises

  • ValueError – raised whenever any of the introduced arguments is not valid or errored.

  • IOError – raised if cryptos object/file was not found or unable to retrieve.

  • RuntimeError – raised if the introduced crypto currency name was not found or did not match any of the existing ones.

  • ConnectionError – raised if connection to Investing.com could not be established.

  • IndexError – raised if crypto historical data was unavailable or not found in Investing.com.

Examples

>>> data = investpy.get_crypto_historical_data(crypto='bitcoin', from_date='01/01/2018', to_date='01/01/2019')
>>> data.head()
               Open     High      Low    Close  Volume Currency
Date
2018-01-01  13850.5  13921.5  12877.7  13444.9   78425      USD
2018-01-02  13444.9  15306.1  12934.2  14754.1  137732      USD
2018-01-03  14754.1  15435.0  14579.7  15156.6  106543      USD
2018-01-04  15156.5  15408.7  14244.7  15180.1  110969      USD
2018-01-05  15180.1  17126.9  14832.4  16954.8  141960      USD
investpy.crypto.get_crypto_information(crypto, as_json=False)

This function retrieves fundamental financial information from the specified crypto currency. The retrieved information from the crypto currency can be valuable as it is additional information that can be used combined with OHLC values, so to determine financial insights from the company which holds the specified crypto currency.

Parameters

  • currency_cross (str) – name of the currency_cross to retrieve recent historical data from.

  • as_json (bool, optional) – optional argument to determine the format of the output data (dict or json).

Returns

The resulting pandas.DataFrame contains the information fields retrieved from Investing.com from the specified crypto currency; it can also be returned as a dict, if argument as_json=True.

If any of the information fields could not be retrieved, that field/s will be filled with None values. If the retrieval process succeeded, the resulting dict will look like:

crypto_information = {
    'Chg (7D)': '-4.63%',
    'Circulating Supply': ' BTC18.10M',
    'Crypto Currency': 'Bitcoin',
    'Currency': 'USD',
    'Market Cap': '$129.01B',
    'Max Supply': 'BTC21.00M',
    'Todays Range': '7,057.8 - 7,153.1',
    'Vol (24H)': '$17.57B'
}

Return type

pandas.DataFrame or dict- crypto_information

Raises

  • ValueError – raised if any of the introduced arguments is not valid or errored.

  • FileNotFoundError – raised if cryptos.csv file was not found or errored.

  • IOError – raised if cryptos.csv file is empty or errored.

  • RuntimeError – raised if scraping process failed while running.

  • ConnectionError – raised if the connection to Investing.com errored (did not return HTTP 200)

investpy.crypto.get_crypto_recent_data(crypto, as_json=False, order='ascending', interval='Daily')

This function retrieves recent historical data from the introduced crypto from Investing.com. So on, the recent data of the introduced crypto will be retrieved and returned as a pandas.DataFrame if the parameters are valid and the request to Investing.com succeeds. Note that additionally some optional parameters can be specified: as_json and order, which let the user decide if the data is going to be returned as a json or not, and if the historical data is going to be ordered ascending or descending (where the index is the date), respectively.

Parameters

  • crypto (str) – name of the crypto currency to retrieve data from.

  • as_json (bool, optional) – to determine the format of the output data, either a pandas.DataFrame if False and a json if True.

  • order (str, optional) – to define the order of the retrieved data which can either be ascending or descending.

  • interval (str, optional) – value to define the historical data interval to retrieve, by default Daily, but it can also be Weekly or Monthly.

Returns

The function can return either a pandas.DataFrame or a json object, containing the retrieved recent data of the specified crypto currency. So on, the resulting dataframe contains the open, high, low, close and volume values for the selected crypto on market days and the currency in which those values are presented.

The resulting recent data, in case that the default parameters were applied, will look like:

Date || Open | High | Low | Close | Volume | Currency
-----||------|------|-----|-------|--------|----------
xxxx || xxxx | xxxx | xxx | xxxxx | xxxxxx | xxxxxxxx

but in case that as_json parameter was defined as True, then the output will be:

{
    name: name,
    recent: [
        {
            date: 'dd/mm/yyyy',
            open: x,
            high: x,
            low: x,
            close: x,
            volume: x,
            currency: x
        },
        ...
    ]
}

Return type

pandas.DataFrame or json

Raises

  • ValueError – raised whenever any of the introduced arguments is not valid or errored.

  • IOError – raised if cryptos object/file was not found or unable to retrieve.

  • RuntimeError – raised if the introduced crypto name was not found or did not match any of the existing ones.

  • ConnectionError – raised if connection to Investing.com could not be established.

  • IndexError – raised if crypto recent data was unavailable or not found in Investing.com.

Examples

>>> data = investpy.get_crypto_recent_data(crypto='bitcoin')
>>> data.head()
              Open     High     Low   Close   Volume Currency
Date
2019-10-25  7422.8   8697.7  7404.9  8658.3  1177632      USD
2019-10-26  8658.4  10540.0  8061.8  9230.6  1784005      USD
2019-10-27  9230.6   9773.2  9081.0  9529.6  1155038      USD
2019-10-28  9530.1   9866.9  9202.5  9207.2  1039295      USD
2019-10-29  9206.5   9531.3  9125.3  9411.3   918477      USD
investpy.crypto.get_cryptos()

This function retrieves all the crypto data stored in cryptos.csv file, which previously was retrieved from Investing.com. Since the resulting object is a matrix of data, the crypto data is properly structured in rows and columns, where columns are the crypto data attribute names.

Note that just some cryptos are available for retrieval, since Investing.com does not provide information from all the available ones, just the main ones.

Returns

The resulting pandas.DataFrame contains all the crypto data from every available crypto coin as indexed in Investing.com from the information previously retrieved by investpy and stored on a csv file.

So on, the resulting pandas.DataFrame will look like:

name | symbol | currency
-----|--------|----------
xxxx | xxxxxx | xxxxxxxx

Return type

pandas.DataFrame - cryptos_df

Raises

  • FileNotFoundError – raised if cryptos.csv file was not found.

  • IOError – raised when cryptos.csv file is missing or empty.

investpy.crypto.get_cryptos_dict(columns=None, as_json=False)

This function retrieves all the crypto information stored in the cryptos.csv file and formats it as a Python dictionary which contains the same information as the file, but every row is a dict and all of them are contained in a list. Note that the dictionary structure is the same one as the JSON structure. Some optional paramaters can be specified such as the columns or as_json, which are the column names that want to be retrieved in case of needing just some columns to avoid unnecessary information load, and whether the information wants to be returned as a JSON object or as a dictionary; respectively.

Note that just some cryptos are available for retrieval, since Investing.com does not provide information from all the available ones, just the main ones.

Parameters

  • columns (list, optional) – column names of the crypto data to retrieve, can be: <name, currency, symbol>

  • as_json (bool, optional) – if True the returned data will be a json object, if False, a list of dict.

Returns

The resulting list of dict contains the retrieved data from every crypto coin as indexed in Investing.com from the information previously retrieved by investpy and stored on a csv file.

In case the information was successfully retrieved, the list of dict will look like:

cryptos_dict = {
    'name': name,
    'currency': currency,
    'symbol': symbol,
}

Return type

list of dict OR json - cryptos_dict

Raises

  • ValueError – raised whenever any of the introduced arguments is not valid.

  • FileNotFoundError – raised if cryptos.csv file was not found.

  • IOError – raised when cryptos.csv file is missing or empty.

investpy.crypto.get_cryptos_list()

This function retrieves all the crypto coin names stored in cryptos.csv file, which contains all the data from the crypto coins as previously retrieved from Investing.com. So on, this function will just return the crypto coin names which will be the main input parameters when it comes to crypto data retrieval functions from investpy.

Note that just some cryptos are available for retrieval, since Investing.com does not provide information from all the available ones, just the main ones.

Returns

The resulting list contains the all the available crypto coin names as indexed in Investing.com from the information previously retrieved by investpy and stored on a csv file.

In case the information was successfully retrieved, the list of crypto coin names will look like:

cryptos_list = ['Bitcoin', 'Ethereum', 'XRP', 'Bitcoin Cash', 'Tether', 'Litecoin', ...]

Return type

list - cryptos_list

Raises

  • FileNotFoundError – raised if cryptos.csv file was not found.

  • IOError – raised when cryptos.csv file is missing or empty.

investpy.crypto.get_cryptos_overview(as_json=False, n_results=100)

This function retrieves an overview containing all the real time data available for the main crypto currencies, such as the names, symbols, current value, etc. as indexed in Investing.com. So on, the main usage of this function is to get an overview on the main crypto currencies, so to get a general view. Note that since this function is retrieving a lot of information at once, by default just the overview of the Top 100 crypto currencies is being retrieved, but an additional parameter called n_results can be specified so to retrieve N results.

Parameters

  • as_json (bool, optional) – optional argument to determine the format of the output data (pandas.DataFrame or json).

  • n_results (int, optional) – number of results to be displayed on the overview table (0-all_cryptos), where all crypto currencies will be retrieved if n_results=None.

Note

The amount of indexed crypto currencies may vary, so if n_results is set to None, all the available crypto currencies in Investing.com while retrieving the overview, will be retrieved and returned.

Returns

The resulting pandas.DataFrame contains all the data available in Investing.com of the main crypto currencies in order to get an overview of it.

If the retrieval process succeeded, the resulting pandas.DataFrame should look like:

name | symbol | price | market_cap | volume24h | total_volume | change24h | change7d | currency
-----|--------|-------|------------|-----------|--------------|-----------|----------|----------
xxxx | xxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxxxxx

Return type

pandas.DataFrame - cryptos_overview

Raises

  • ValueError – raised if any of the introduced arguments is not valid or errored.

  • IOError – raised if data could not be retrieved due to file error.

  • RuntimeError – raised it no overview results could be retrieved from Investing.com.

  • ConnectionError – raised if GET requests does not return 200 status code.

investpy.crypto.search_cryptos(by, value)

This function searches cryptos by the introduced value for the specified field. This means that this function is going to search if there is a value that matches the introduced one for the specified field which is the cryptos.csv column name to search in. Available fields to search cryptos are ‘name’ and ‘symbol’.

Parameters

  • by (str) – name of the field to search for, which is the column name which can be: ‘name’ or ‘symbol’.

  • value (str) – value of the field to search for, which is the value that is going to be searched.

Returns

The resulting pandas.DataFrame contains the search results from the given query, which is any match of the specified value in the specified field. If there are no results for the given query, an error will be raised, but otherwise the resulting pandas.DataFrame will contain all the available cryptos that match the introduced query.

Return type

pandas.DataFrame - search_result

Raises

  • ValueError – raised if any of the introduced parameters is not valid or errored.

  • FileNotFoundError – raised if cryptos.csv file is missing.

  • IOError – raised if data could not be retrieved due to file error.

  • RuntimeError – raised if no results were found for the introduced value in the introduced field.