Exercise 7

1. Create 500 random temperature readings for six cities over a season and then plot the generated data using Matplotlib.

import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline

data = np.random.RandomState(0)
season1 = np.cumsum(data.rand(500, 6), 0)

#season1 = np.random.rand(500, 6)

# plot using matplotlib
#plt.style.use('classic')
plt.plot(season1)
plt.legend('ABCDEF', ncol=2, loc='upper left')

<matplotlib.legend.Legend at 0x1cb74015df0>

1. Load the well-known Iris data set, which lists measurements of petals and sepals of three iris species. Then plot the correlations between each pair using the .pairplot() method.

import seaborn as sns

# load the iris dataset
iris = sns.load_dataset('iris')
iris.head()

	sepal_length	sepal_width	petal_length	petal_width	species
0	5.1	3.5	1.4	0.2	setosa
1	4.9	3.0	1.4	0.2	setosa
2	4.7	3.2	1.3	0.2	setosa
3	4.6	3.1	1.5	0.2	setosa
4	5.0	3.6	1.4	0.2	setosa

# plot the iris data
sns.pairplot(iris, hue='species', size=2.5)

C:\Users\Asmaliza\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.9_qbz5n2kfra8p0\LocalCache\local-packages\Python39\site-packages\seaborn\axisgrid.py:1969: UserWarning: The `size` parameter has been renamed to `height`; please update your code.
  warnings.warn(msg, UserWarning)

<seaborn.axisgrid.PairGrid at 0x1cb0c7ca7c0>

1. Load the well-known Tips data set, which shows the number of tips received by restaurant staff based on various indicator data; then plot the percentage of tips per bill according to staff gender.

# load the tips dataset
tips = sns.load_dataset("tips")
tips.head()

	total_bill	tip	sex	smoker	day	time	size
0	16.99	1.01	Female	No	Sun	Dinner	2
1	10.34	1.66	Male	No	Sun	Dinner	3
2	21.01	3.50	Male	No	Sun	Dinner	3
3	23.68	3.31	Male	No	Sun	Dinner	2
4	24.59	3.61	Female	No	Sun	Dinner	4

# calculate the percentage of tips per bill
tips['Tips Percentage'] = (tips['tip'] / tips['total_bill']) * 100
tips.head()

	total_bill	tip	sex	smoker	day	time	size	Tips Percentage
0	16.99	1.01	Female	No	Sun	Dinner	2	5.944673
1	10.34	1.66	Male	No	Sun	Dinner	3	16.054159
2	21.01	3.50	Male	No	Sun	Dinner	3	16.658734
3	23.68	3.31	Male	No	Sun	Dinner	2	13.978041
4	24.59	3.61	Female	No	Sun	Dinner	4	14.680765

# plot the data
grid = sns.FacetGrid(tips, row='sex', col='time', margin_titles=True)
grid.map(plt.hist, "Tips Percentage", bins=np.linspace(0,40,15))

<seaborn.axisgrid.FacetGrid at 0x1cb79f38400>

1. Load the well-known Tips data set, which shows the number of tips received by restaurant staff based on various indicator data; then implement the factor plots to visualize the total bill per day according to staff gender.

tips = sns.load_dataset('tips')
with sns.axes_style(style='ticks'):
    g = sns.factorplot("day", "total_bill", "sex", data=tips, kind="box")
    g.set_axis_labels("Bill Day", "Total Bill Amount")

C:\Users\Asmaliza\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.9_qbz5n2kfra8p0\LocalCache\local-packages\Python39\site-packages\seaborn\categorical.py:3714: UserWarning: The `factorplot` function has been renamed to `catplot`. The original name will be removed in a future release. Please update your code. Note that the default `kind` in `factorplot` (`'point'`) has changed `'strip'` in `catplot`.
  warnings.warn(msg)
C:\Users\Asmaliza\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.9_qbz5n2kfra8p0\LocalCache\local-packages\Python39\site-packages\seaborn\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y, hue. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.
  warnings.warn(

1. Reimplement the previous exercise using the Seaborn joint plot distributions.

tips = sns.load_dataset('tips')
with sns.axes_style('white'):
    sns.jointplot( "total_bill", "tip", data=tips, kind='hex')

C:\Users\Asmaliza\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.9_qbz5n2kfra8p0\LocalCache\local-packages\Python39\site-packages\seaborn\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.
  warnings.warn(