| Name | ben-future-value JSON |
| Version |
1.0.1
JSON |
| download |
| home_page | None |
| Summary | A package to assist in calculating future value |
| upload_time | 2024-09-14 22:56:41 |
| maintainer | None |
| docs_url | None |
| author | Ben Payton |
| requires_python | None |
| license | None |
| keywords |
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|
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No requirements were recorded.
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# Project Description
[Link_To_Wiki](https://github.com/Ben-Payton/ben_future_value/wiki)
This is a package for calculating future values and debt payoff in python.
Generally this is a small package so people can learn how to install and use packages.
It is meant to pair well with [matplotlib](https://matplotlib.org/) and [seaborn](https://seaborn.pydata.org/) they are listed as dependancies to ensure they are installed.
# How to install and use
In the command line type:
`pip install ben-future-value`
Once installed then use by importing at the top of your python code.
Below is an example of how you might generate a graph to compare outcomes of different interest rates.
```python
# Here we import packages, the first one is for making graphs
# the second one allows us to calculate our future values
# The third one allows us to make our graphs a little prettier with less code.
import matplotlib.pyplot as plt
import ben_future_value as bfv
import seaborn as sns
#These next lines makes our graph pretty later. You don't need them.
sns.set_context("notebook")
sns.set_style("darkgrid")
# These variables are for convenience of editing later.
NUMBER_OF_YEARS = 25
MATCHES_PER_YEAR = 4
PRINCIPLE_VALUE = 1000.00
AMMOUNT_CONTRIBUTED_PER_MATCH = 100.00
PERCENT_INCREASE_ONE = 5.0
PERCENT_INCREASE_TWO = 8.5
PERCENT_INCREASE_THREE = 12.0
# Here we use the ben_future_value package to calculate future values
high_yield_savings = bfv.Future_Value(
PRINCIPLE_VALUE,
PERCENT_INCREASE_ONE,
AMMOUNT_CONTRIBUTED_PER_MATCH,
NUMBER_OF_YEARS,
MATCHES_PER_YEAR
)
low_interest_investment = bfv.Future_Value(
PRINCIPLE_VALUE,
PERCENT_INCREASE_TWO,
AMMOUNT_CONTRIBUTED_PER_MATCH,
NUMBER_OF_YEARS,
MATCHES_PER_YEAR
)
average_interest_investment = bfv.Future_Value(
PRINCIPLE_VALUE,
PERCENT_INCREASE_THREE,
AMMOUNT_CONTRIBUTED_PER_MATCH,
NUMBER_OF_YEARS,
MATCHES_PER_YEAR
)
# Next we plot our future values
plt.plot(high_yield_savings.get_future_values())
plt.plot(low_interest_investment.get_future_values())
plt.plot(average_interest_investment.get_future_values())
plt.legend(
[
"High Yield Savings (" + str(PERCENT_INCREASE_ONE) + "%)",
"Low Interest Investment (" + str(PERCENT_INCREASE_TWO) + "%)",
"Average Interest Investment (" + str(PERCENT_INCREASE_THREE) + "%)"
]
)
# These next two lines add axis titles
plt.xlabel("Number of Matches")
plt.ylabel("Dollar Value")
# This shows out graph when we run out code
plt.show()
```
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"description": "# Project Description\n\n[Link_To_Wiki](https://github.com/Ben-Payton/ben_future_value/wiki)\n\nThis is a package for calculating future values and debt payoff in python.\nGenerally this is a small package so people can learn how to install and use packages. \nIt is meant to pair well with [matplotlib](https://matplotlib.org/) and [seaborn](https://seaborn.pydata.org/) they are listed as dependancies to ensure they are installed.\n\n\n# How to install and use\n\nIn the command line type:\n\n`pip install ben-future-value`\n\nOnce installed then use by importing at the top of your python code.\n\nBelow is an example of how you might generate a graph to compare outcomes of different interest rates.\n\n```python\n# Here we import packages, the first one is for making graphs\n# the second one allows us to calculate our future values\n# The third one allows us to make our graphs a little prettier with less code. \nimport matplotlib.pyplot as plt\nimport ben_future_value as bfv\nimport seaborn as sns\n\n#These next lines makes our graph pretty later. You don't need them.\nsns.set_context(\"notebook\")\nsns.set_style(\"darkgrid\")\n\n\n# These variables are for convenience of editing later.\nNUMBER_OF_YEARS = 25\nMATCHES_PER_YEAR = 4\nPRINCIPLE_VALUE = 1000.00\nAMMOUNT_CONTRIBUTED_PER_MATCH = 100.00\n\nPERCENT_INCREASE_ONE = 5.0\nPERCENT_INCREASE_TWO = 8.5\nPERCENT_INCREASE_THREE = 12.0\n\n\n# Here we use the ben_future_value package to calculate future values\nhigh_yield_savings = bfv.Future_Value(\n PRINCIPLE_VALUE,\n PERCENT_INCREASE_ONE,\n AMMOUNT_CONTRIBUTED_PER_MATCH,\n NUMBER_OF_YEARS,\n MATCHES_PER_YEAR\n)\n\nlow_interest_investment = bfv.Future_Value(\n PRINCIPLE_VALUE,\n PERCENT_INCREASE_TWO,\n AMMOUNT_CONTRIBUTED_PER_MATCH,\n NUMBER_OF_YEARS,\n MATCHES_PER_YEAR\n)\n\naverage_interest_investment = bfv.Future_Value(\n PRINCIPLE_VALUE,\n PERCENT_INCREASE_THREE,\n AMMOUNT_CONTRIBUTED_PER_MATCH,\n NUMBER_OF_YEARS,\n MATCHES_PER_YEAR\n)\n\n\n# Next we plot our future values\nplt.plot(high_yield_savings.get_future_values())\nplt.plot(low_interest_investment.get_future_values())\nplt.plot(average_interest_investment.get_future_values())\n\nplt.legend(\n [\n \"High Yield Savings (\" + str(PERCENT_INCREASE_ONE) + \"%)\",\n \"Low Interest Investment (\" + str(PERCENT_INCREASE_TWO) + \"%)\",\n \"Average Interest Investment (\" + str(PERCENT_INCREASE_THREE) + \"%)\"\n ]\n)\n\n# These next two lines add axis titles\nplt.xlabel(\"Number of Matches\")\nplt.ylabel(\"Dollar Value\")\n# This shows out graph when we run out code\nplt.show()\n```\n\n",
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