partypy¶
Submodules¶
Package Contents¶
Functions¶
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Simulate guest attendance at a party. |
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Plot a histogram of simulation results. |
Return a dataframe of 100 party guests. |
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partypy.simulate_party(p, n_simulations=500)[source]¶ Simulate guest attendance at a party.
The attendance of each guest is treated as a Bernoulli random variable with probability of attendance p. The total number of attending guests is summed up for each n_simulations.
- Parameters
p (float or array_like of floats) – Probability of guest attendance, >= 0 and <=1.
n_simulations (int, optional) – Number of simulations to run. By default, 500.
- Returns
DataFrame with total number of guests per simulation.
- Return type
pandas.DataFrame
Examples
>>> simulate_party([0.1, 0.5, 0.9], n_simulations=5) Total guests Simulation 1 2 2 2 3 2 4 2 5 2
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partypy.plot_simulation(results)[source]¶ Plot a histogram of simulation results.
- Parameters
results (pandas.DataFrame) – DataFrame of simulation results from partpy.simulate_party()
- Returns
Histogram of simulation results.
- Return type
altair.Chart
Examples
>>> from partypy.simulate import simulate_party >>> from partypy.plotting import plot_simulation >>> results = simulate([0.1, 0.5, 0.9]) >>> plot_simulation(results) altair.Chart
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partypy.load_party()[source]¶ Return a dataframe of 100 party guests.
- Contains the following fields:
name 100 non-null object probability_of_attendance 100 non-null float
- Returns
DataFrame of party guest names and probabilities of attendance.
- Return type
pandas.DataFrame
Examples
>>> data = load_party() >>> data.head() name probability_of_attendance 0 Donovan Willis 0.70 1 Jocelyn Navarro 0.70 2 Houston Stein 0.90 3 Carlos Mullins 0.50 4 Bridger Pruitt 0.70