Alt gruplarla kutu grafiği

Bu egzersizde, gençlere uygulanan bir anketten gelen yanıtları içeren veri kümesine bakacağız. Gençlere sorulan sorulardan biri şuydu: "Evcil hayvanlarla ilgileniyor musun?" Cinsiyeti sabit tutarak, "evet" yanıtını verenlerin yaş dağılımının "hayır" diyenlere göre daha yüksek mi yoksa daha düşük mü olma eğiliminde olduğunu keşfedelim.

Bu egzersiz

Seaborn ile Veri Görselleştirmeye Giriş

kursunun bir parçasıdır

Kursu Görüntüle

Egzersiz talimatları

Renk paletini "Blues" olarak ayarla.
Kutu grafikleri "Interested in Pets" değişkenine göre renklendirmek için alt gruplar ekle.
FacetGrid nesnesi g için başlığı "Age of Those Interested in Pets vs. Not" olarak ayarla.
Grafiği bir Matplotlib fonksiyonu kullanarak göster.

Uygulamalı interaktif egzersiz

Bu örnek kodu tamamlayarak bu egzersizi bitirin.

# Set palette to "Blues"
____

# Adjust to add subgroups based on "Interested in Pets"
g = sns.catplot(x="Gender",
                y="Age", data=survey_data, 
                kind="box", hue=____)

# Set title to "Age of Those Interested in Pets vs. Not"
____

# Show plot
plt.____

Kodu Düzenle ve Çalıştır

Bu egzersiz

Seaborn ile Veri Görselleştirmeye Giriş

kursunun bir parçasıdır

InicianteNível de habilidade

4.9+

Kursa Ücretsiz Başlayın

What is Seaborn, and when should you use it? In this chapter, you will find out! Plus, you will learn how to create scatter plots and count plots with both lists of data and pandas DataFrames. You will also be introduced to one of the big advantages of using Seaborn - the ability to easily add a third variable to your plots by using color to represent different subgroups.

Exercise 1: Introduction to Seaborn Exercise 2: Making a scatter plot with lists Exercise 3: Making a count plot with a list Exercise 4: Using pandas with Seaborn Exercise 5: "Tidy" vs. "untidy" data Exercise 6: Making a count plot with a DataFrame Exercise 7: Adding a third variable with hue Exercise 8: Hue and scatter plots Exercise 9: Hue and count plots

In this chapter, you will create and customize plots that visualize the relationship between two quantitative variables. To do this, you will use scatter plots and line plots to explore how the level of air pollution in a city changes over the course of a day and how horsepower relates to fuel efficiency in cars. You will also see another big advantage of using Seaborn - the ability to easily create subplots in a single figure!

Exercise 1: Introduction to relational plots and subplots Exercise 2: Creating subplots with col and row Exercise 3: Creating two-factor subplots Exercise 4: Customizing scatter plots Exercise 5: Changing the size of scatter plot points Exercise 6: Changing the style of scatter plot points Exercise 7: Introduction to line plots Exercise 8: Interpreting line plots Exercise 9: Visualizing standard deviation with line plots Exercise 10: Plotting subgroups in line plots

Categorical variables are present in nearly every dataset, but they are especially prominent in survey data. In this chapter, you will learn how to create and customize categorical plots such as box plots, bar plots, count plots, and point plots. Along the way, you will explore survey data from young people about their interests, students about their study habits, and adult men about their feelings about masculinity.

Exercise 1: Count plots and bar plots Exercise 2: Count plots Exercise 3: Bar plots with percentages Exercise 4: Customizing bar plots Exercise 5: Box plots Exercise 6: Create and interpret a box plot Exercise 7: Omitting outliers Exercise 8: Adjusting the whiskers Exercise 9: Point plots Exercise 10: Customizing point plots Exercise 11: Point plots with subgroups

In this final chapter, you will learn how to add informative plot titles and axis labels, which are one of the most important parts of any data visualization! You will also learn how to customize the style of your visualizations in order to more quickly orient your audience to the key takeaways. Then, you will put everything you have learned together for the final exercises of the course!

Exercise 1: Grafik stilini ve rengini değiştirme Exercise 2: Stil ve paleti değiştirme Exercise 3: Ölçeği değiştirme Exercise 4: Özel bir palet kullanma Exercise 5: Başlıklar ve etiketler ekleme: Bölüm 1 Exercise 6: FacetGrid'ler ve AxesSubplot'lar Exercise 7: Bir FacetGrid nesnesine başlık ekleme Exercise 8: Başlıklar ve etiketler ekleme: Bölüm 2 Exercise 9: Başlık ve eksen etiketleri ekleme Exercise 10: x-tick etiketlerini döndürme Exercise 11: Hepsini bir araya getirmek Exercise 12: Alt gruplarla kutu grafiği

Geçerli Egzersiz

Exercise 13: Alt gruplar ve alt grafiklerle çubuk grafik Exercise 14: Tebrikler! Sırada ne var?