Finparse
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
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