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Parse financial strings to numbers

Project description

Finparse

pypi python pytest coverage maintainability

Parse financial strings to number objects

Installation

pip install finparse

Usage

import finparse

finparse.parse("$1,234,567.89")
# => 1234567.89

finparse.parse("€1.234.567,89", decimal=",")
# => 1234567.89

finparse.parse("($1,234,567.89)")
# => -1234567.89

import decimal

finparse.parse("$1,234,567.89", cast=decimal.Decimal)
# => Decimal('1234567.89')

Pandas

Pandas' read_csv() function provdides a converters argument that applies a function to the given column.

Using the example CSV file ./tests/example.csv, we can see the following behavior:

import pandas

df = pandas.read_csv('./tests/example.csv')

print(df)
# =>        Acct     Balance
#    0   Savings  $1,234.567
#    1  Checking    ($0.987)

With the converters argument we can parse these values to floats:

import finparse
import pandas

df = pandas.read_csv('./tests/example.csv', converters={'Balance': finparse.parse})

print(df)
# =>        Acct   Balance
#    0   Savings  1234.567
#    1  Checking    -0.987

Project details


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