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Joshuaek/SimpleBusinessCaseForecast.ipynb

Created March 2, 2020 18:27
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SimpleBusinessCaseForecast.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"\n",
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt \n",
"import matplotlib.ticker as mtick\n",
"\n",
"plt.rcParams[\"figure.figsize\"] = [20, 10]\n",
"plt.style.use('bmh')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>forecast_licences</th>\n",
" <th>live_contracts</th>\n",
" <th>total_sales</th>\n",
" <th>Bicky Box0</th>\n",
" <th>Bicky Box1</th>\n",
" <th>Bicky Box2</th>\n",
" <th>Bicky Box3</th>\n",
" <th>Bicky Box4</th>\n",
" <th>Bicky Box5</th>\n",
" <th>Bicky Box6</th>\n",
" <th>...</th>\n",
" <th>Cboccy Bicky Box50</th>\n",
" <th>Cboccy Bicky Box51</th>\n",
" <th>Cboccy Bicky Box52</th>\n",
" <th>Cboccy Bicky Box53</th>\n",
" <th>Cboccy Bicky Box54</th>\n",
" <th>Cboccy Bicky Box55</th>\n",
" <th>Cboccy Bicky Box56</th>\n",
" <th>Cboccy Bicky Box57</th>\n",
" <th>Cboccy Bicky Box58</th>\n",
" <th>Cboccy Bicky Box59</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <td>2020-01-31</td>\n",
" <td>24.99</td>\n",
" <td>2.0</td>\n",
" <td>24.99</td>\n",
" <td>9.99</td>\n",
" <td>0.00</td>\n",
" <td>0.00</td>\n",
" <td>0.00</td>\n",
" <td>0.00</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <td>2020-02-29</td>\n",
" <td>49.98</td>\n",
" <td>4.0</td>\n",
" <td>74.97</td>\n",
" <td>9.99</td>\n",
" <td>9.99</td>\n",
" <td>0.00</td>\n",
" <td>0.00</td>\n",
" <td>0.00</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <td>2020-03-31</td>\n",
" <td>74.97</td>\n",
" <td>6.0</td>\n",
" <td>149.94</td>\n",
" <td>9.99</td>\n",
" <td>9.99</td>\n",
" <td>9.99</td>\n",
" <td>0.00</td>\n",
" <td>0.00</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
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" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <td>2020-04-30</td>\n",
" <td>99.96</td>\n",
" <td>8.0</td>\n",
" <td>249.90</td>\n",
" <td>9.99</td>\n",
" <td>9.99</td>\n",
" <td>9.99</td>\n",
" <td>9.99</td>\n",
" <td>0.00</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <td>2020-05-31</td>\n",
" <td>124.95</td>\n",
" <td>10.0</td>\n",
" <td>374.85</td>\n",
" <td>9.99</td>\n",
" <td>9.99</td>\n",
" <td>9.99</td>\n",
" <td>9.99</td>\n",
" <td>9.99</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 123 columns</p>\n",
"</div>"
],
"text/plain": [
" forecast_licences live_contracts total_sales Bicky Box0 \\\n",
"2020-01-31 24.99 2.0 24.99 9.99 \n",
"2020-02-29 49.98 4.0 74.97 9.99 \n",
"2020-03-31 74.97 6.0 149.94 9.99 \n",
"2020-04-30 99.96 8.0 249.90 9.99 \n",
"2020-05-31 124.95 10.0 374.85 9.99 \n",
"\n",
" Bicky Box1 Bicky Box2 Bicky Box3 Bicky Box4 Bicky Box5 \\\n",
"2020-01-31 0.00 0.00 0.00 0.00 0.0 \n",
"2020-02-29 9.99 0.00 0.00 0.00 0.0 \n",
"2020-03-31 9.99 9.99 0.00 0.00 0.0 \n",
"2020-04-30 9.99 9.99 9.99 0.00 0.0 \n",
"2020-05-31 9.99 9.99 9.99 9.99 0.0 \n",
"\n",
" Bicky Box6 ... Cboccy Bicky Box50 Cboccy Bicky Box51 \\\n",
"2020-01-31 0.0 ... 0.0 0.0 \n",
"2020-02-29 0.0 ... 0.0 0.0 \n",
"2020-03-31 0.0 ... 0.0 0.0 \n",
"2020-04-30 0.0 ... 0.0 0.0 \n",
"2020-05-31 0.0 ... 0.0 0.0 \n",
"\n",
" Cboccy Bicky Box52 Cboccy Bicky Box53 Cboccy Bicky Box54 \\\n",
"2020-01-31 0.0 0.0 0.0 \n",
"2020-02-29 0.0 0.0 0.0 \n",
"2020-03-31 0.0 0.0 0.0 \n",
"2020-04-30 0.0 0.0 0.0 \n",
"2020-05-31 0.0 0.0 0.0 \n",
"\n",
" Cboccy Bicky Box55 Cboccy Bicky Box56 Cboccy Bicky Box57 \\\n",
"2020-01-31 0.0 0.0 0.0 \n",
"2020-02-29 0.0 0.0 0.0 \n",
"2020-03-31 0.0 0.0 0.0 \n",
"2020-04-30 0.0 0.0 0.0 \n",
"2020-05-31 0.0 0.0 0.0 \n",
"\n",
" Cboccy Bicky Box58 Cboccy Bicky Box59 \n",
"2020-01-31 0.0 0.0 \n",
"2020-02-29 0.0 0.0 \n",
"2020-03-31 0.0 0.0 \n",
"2020-04-30 0.0 0.0 \n",
"2020-05-31 0.0 0.0 \n",
"\n",
"[5 rows x 123 columns]"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"class contract:\n",
" \n",
" def __init__(self, start_month, payment_frequency, value, term, contract_name, increase_period=1, increase_percentage=0):\n",
" self.start_month = start_month # The month (zero based int) at which the contract starts \n",
" self.payment_frequency = payment_frequency # The frequency of payments (e.g. 1 for monthly, 3 for quarterly, 12 for annually)\n",
" self.value = value # The money recieved from the contract\n",
" self.term = term # The duration of the contract in months\n",
" self.contract_name = contract_name # An identifier for the contract\n",
" self.increase_period = increase_period # Optional frequency of price increases (e.g. 12 for an annual inflation)\n",
" self.increase_percentage = increase_percentage # Optional percentage increase (e.g. 2.5 for a 2.5% price increase)\n",
"\n",
"\n",
"class forecast:\n",
" \n",
" def __init__(self, start_date, number_of_months):\n",
" self.start_date = start_date\n",
" self.number_of_months = number_of_months\n",
" self.months = pd.date_range('2020-01', periods=60, freq='M')\n",
" \n",
" self.contracts = []\n",
" \n",
" self.df = pd.DataFrame(index=self.months)\n",
" self.df['forecast_licences'] = np.zeros(number_of_months)\n",
" self.df['live_contracts'] = np.zeros(number_of_months)\n",
" self.df['total_sales'] = np.zeros(number_of_months)\n",
"\n",
" \n",
" def add_contract(self, contract):\n",
" # Adds a new contract to the forecast\n",
" \n",
" self.df[contract.contract_name] = np.zeros(self.number_of_months)\n",
" self.contracts.append(contract)\n",
" \n",
" for m in range(contract.start_month, contract.start_month + contract.term, contract.payment_frequency):\n",
" try:\n",
" increase = (contract.increase_percentage * int(m / contract.increase_period) / 100) * contract.value \n",
" self.df.loc[self.months[m]][contract.contract_name] = contract.value + increase\n",
" self.df.loc[self.months[m]]['live_contracts'] += 1\n",
" except IndexError:\n",
" pass\n",
" \n",
" \n",
" def result(self):\n",
" # Ensure all calculations are done and return the dataframe\n",
" \n",
" # First, sum all licence columns to get the total earned in that month from all live contracts\n",
" self.df['forecast_licences'] = self.df[[c.contract_name for c in self.contracts]].sum(axis=1)\n",
" \n",
" # Secondly, calculate a cumulative total licence sales\n",
" self.df['total_sales'] = self.df.forecast_licences.cumsum()\n",
" \n",
" return self.df\n",
" \n",
" def project(self, start_month, contract_frequency, payment_frequency, number_of_contracts, value, term, name, increase_period=1, increase_percentage=0):\n",
" \n",
" for m in range(start_month, self.number_of_months - start_month, contract_frequency):\n",
" c = contract(m, payment_frequency, value, term, name + str(m), increase_period, increase_percentage)\n",
" self.add_contract(c)\n",
" \n",
" \n",
"# Our main assumptions \n",
"good_forecast = forecast('2020-01',60)\n",
"\n",
"good_forecast.project(0, 1, 1, 25, 9.99, 24, 'Bicky Box')\n",
"good_forecast.project(0, 1, 1, 10, 15, 24, 'Cboccy Bicky Box')\n",
"\n",
"\n",
"# What if things don't go so well?\n",
"bad_forecast = forecast('2020-01',60)\n",
"\n",
"bad_forecast.project(0, 1, 1, 15, 7.50, 12, 'Bicky Box')\n",
"bad_forecast.project(0, 1, 1, 5, 12.50, 12, 'Cboccy Bicky Box')\n",
"\n",
"\n",
"\n",
"good_forecast.result().head()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0.5, 1.0, 'Bicky Box Licence Revenue Forecast - Three Years inc. pessamistic outcome')"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1440x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"ax = good_forecast.result().total_sales.plot()\n",
"\n",
"bad_forecast.result().total_sales.plot(ax=ax)\n",
"\n",
"fmt = '£{x:,.0f}'\n",
"tick = mtick.StrMethodFormatter(fmt)\n",
"ax.yaxis.set_major_formatter(tick) \n",
"\n",
"plt.title('Bicky Box Licence Revenue Forecast - Three Years inc. pessamistic outcome')"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.5"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
@entzyeung
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entzyeung commented Dec 26, 2020 •
edited

hello Joshuaek,
thank you for the tutorial, it is great.
but is there something missing in the def add_contract method?
i tried it and it adds nothing to the forecast data frame, or am i missing something?
Screen Shot 2020-12-26 at 11 49 55 AM

regards

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