Data Science Tools for Monetary Information and Conversions.
This package is primarily intended to be used in the domain of Data Science to simplify the process of analysing data sets which contain money information. Often, the financial information within, and very often between, data sets is be separated in time (inflation), currency (conversion) as well as the ways in which these sources refer to the currency being used (e.g., ISO Alpha2 Codes vs. Currency Codes). Conventionally, this has required handcrafting a solution to control for these differences on a case-by-case basis. EasyMoney is intended to streamline this process to make comparisons across these dimensions extremely simple and straightforward.
- Computing Inflation
- Currency Conversion
- Adjusting a given currency for Inflation
- ‘Normalizing’ a currency, i.e., adjust for inflation and then convert to a base currency.
- Relating ISO Alpha2/3 Codes, Currency Codes and a region’s Natural Name.
NOTICE: THIS TOOL IS FOR INFORMATION PURPOSES ONLY.
$ pip3 install easymoney
Note: EasyMoney requires Python 3.4 or later.
Import the tool
from easymoney.money import EasyPeasy
Create an instance of the EasyPeasy Class
ep = EasyPeasy()
Prototypical Conversion Problems
ep.currency_converter(amount = 100, from_currency = "USD", to_currency = "EUR", pretty_print = True) # 88.75 EUR
Adjust for Inflation and Convert
ep.normalize(amount = 100, currency = "USD", from_year = 2010, to_year = "latest", base_currency = "CAD", pretty_print = True) # 140.66 CAD
Convert Currency in a more Natural Way
ep.currency_converter(amount = 100, from_currency = "Canada", to_currency = "Ireland", pretty_print = True) # 68.58 EUR
Handling Common Currencies
ep.currency_converter(amount = 100, from_currency = "France", to_currency = "Germany", pretty_print = True) # 100.00 EUR
EasyMoney understands that these two nations share a common currency.
ep.normalize(amount = 100, currency = "France", from_year = 2010, to_year = "latest", base_currency = "USD", pretty_print = True) # 118.98 USD
ep.normalize(amount = 100, currency = "Germany", from_year = 2010, to_year = "latest", base_currency = "USD", pretty_print = True) # 120.45 USD
EasyMoney also understands that, while these two nations may share a common currency, inflation may differ.
It’s easy to explore the terminology understood by EasyPeasy, as well as the dates for which data is available, with options().
ep.options(info = 'all', pretty_print = True, overlap_only = True)
|Region||Currency||Alpha2||Alpha3||Inflation Range||Exchange Range||Overlap||Transitions|
|Australia||AUD||AU||AUS||[1960, 2015]||[1999-01-04 : 2016-09-12]||[1999-01-04 : 2015-12-31]|
|Austria||EUR||AT||AUT||[1960, 2015]||[1999-01-04 : 2016-09-12]||[1999-01-04 : 2015-12-31]||1999 (ATS to EUR)|
|Belgium||EUR||BE||BEL||[1960, 2015]||[1999-01-04 : 2016-09-12]||[1999-01-04 : 2015-12-31]||1999 (BEF to EUR)|
Above, the InflationRange and ExchangeRange columns provide the range of dates for which inflation and exchange rate information is available, respectively. The Overlap column shows the range of dates shared by these two columns. Additionally, the dates of known transitions from one currency to another are also provided.
To gain access to a summary of the exchange data alone, ‘exchange’ can be passed to info. Similarly, ‘inflation’ can be passed to inspect inflation information separately.
# Currency Information Alone ep.options(info = 'exchange', pretty_print = True) # Inflation Information Alone ep.options(info = 'inflation', pretty_print = True)
Changing pretty_print to False will return the information in options() as a Pandas DataFrame.
inflation_df = ep.options(info = 'inflation', pretty_print = False)
It is also possible to simply obtain a list of regions for which inflation information is available.
inflation_list = ep.options(info = 'inflation', rformat = 'list', pretty_print = False)
This can also be done for exchange rate information.
currency_list = ep.options(info = 'exchange', rformat = 'list', pretty_print = False)
It’s also straightforward to gain access to the databases used by EasyPeasy().
To see all of the International Organization for Standardization (ISO) Alpha2 and Alpha3 codes (along with a region’s natural name) currently cached:
To see all of the known transitions from one currency to another:
To see the raw Exchange Rate information currently cached:
To see the raw Consumer Price Index (CPI) information currently cached:
Finally, to see the relationships between Country Names, ISO Alpha2/3 Codes and Currency Codes currently understood by EasyPeasy():
The databases used by EasyPeasy() can be saved disk so they can be used offline or modified. To do so, one can simply pass a directory when creating an instance of the EasyPeasy() class.
ep = EasyPeasy('/path/of/your/choosing')
If this directory does not contain any of the required databases, it will be populated with them. Conversely, if the the directory already contains some of the required databases, EasyPeasy() will automagically read in the existing databases and generate only those databases that are missing.
This software is provided under a BSD License.
- Consumer price index (2010 =
- Source: International Monetary Fund (IMF), International Financial
- ALL INFLATION-RELATED RESULTS OBTAINED FROM EASYMONEY (INCLUDING, BUT NOT NECESSARILY LIMITED TO, INFLATION RATE AND NORMALIZATION) ARE THE RESULT OF CALCULATIONS BASED ON IMF DATA. THESE RESULTS ARE NOT A DIRECT REPORTING OF IMF-PROVIDED DATA.
- Source: International Monetary Fund (IMF), International Financial Statistics.
- Euro foreign exchange reference rates - European Central
- Source: European Central Bank (ECB).
- The ECB data used here can be obtained directly from the link provided above.
- Rates are updated by the ECB around 16:00 CET.
- The ECB states, clearly, that usage for transaction purposes is strongly discouraged. This sentiment is echoed here; as stated above, this tool is intended to be for information purposes only.
- ALL EXCHANGE RATE-RELATED RESULTS OBTAINED FROM EASYMONEY (INCLUDING, BUT NOT NECESSARILY LIMITED TO, CURRENCY CONVERSION AND NORMALIZATION) ARE THE RESULT OF CALCULATIONS BASED ON ECB DATA. THESE RESULTS ARE NOT A DIRECT REPORTING OF ECB-PROVIDED DATA.
- Source: European Central Bank (ECB).
† Sherouse, Oliver (2014). Wbdata. Arlington, VA.
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