Lære Visualization: First Steps

An essential tool for Data Analysts is visualization. The first one here is .barplot(). To use the tools you need to import the libraries, look at the syntax:

import matplotlib.pyplot as plt
import seaborn as sns

We will use the second one, Seaborn, but it is based on Matplotlib, so we need to import two of them. Look at the dataset that we used to use for examples:

Our task is to visualize experience_level and the mean salary for each of them. Look at the code:


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import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd

df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/INTRO+to+Python/ds_salaries.csv', index_col = 0)
df = df[['experience_level', 'salary']].groupby(['experience_level']).median().reset_index()
sns.barplot(data = df, x = 'experience_level', y = 'salary')
plt.show()

Here, is the output

barplot

Look at the sixth line of code:

df = df[['experience_level', 'salary']].groupby(['experience_level']).median().reset_index()

Here you can recognize the new function .reset_index(). It is easy and just transforms the result of .groupby() function into the regular dataset. Look at the pictures (the first one is before and the second one is after):

Then we will move to the seventh line of code.

sns.barplot(data = df, x = 'experience_level', y = 'salary')

sns - referring to seaborn library.
barplot the type of plot.
data = df the DataFrame.
x = 'experience_level' the column for x-axis.
y = 'salary' the column for y-axis.

Move to the eighth line of code:

plt.show()

Function from the matplotlib library to output the plot.

Opgave

Swipe to start coding

Visualize the sum of money you receive from users depending on their subscription plan.

Import the seaborn with the sns alias.
Import the matplotlib.pyplot with the plt alias.
Prepare data for visualization using the .groupby() function:

Extract columns 'plan', 'price'.
Group by column plan.
Calculate the sum of all prices for each plan.
Reset indices.

Create the barplot using the seaborn:

Use df as the data argument
Use the 'plan' column for the x-axis
Use the 'price' column for the y-axis.

Output the plot.

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Sektion 3. Kapitel 16

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