Menambahkan judul dan label sumbu

Mari lanjut melihat himpunan data miles per gallon. Kali ini kita akan membuat plot garis untuk menjawab pertanyaan: Bagaimana perubahan rata-rata miles per gallon yang dicapai mobil dari waktu ke waktu untuk masing-masing dari tiga asal wilayah? Untuk meningkatkan keterbacaan plot ini, kita akan menambahkan judul dan label sumbu yang lebih informatif.

Pada kode yang disediakan, kita membuat plot garis menggunakan fungsi lineplot(). Perhatikan bahwa lineplot() tidak mendukung pembuatan subplot, sehingga fungsi ini mengembalikan objek AxesSubplot alih-alih objek FacetGrid.

Kita sudah mengimpor Seaborn sebagai sns dan matplotlib.pyplot sebagai plt.

Latihan ini adalah bagian dari kursus

Pengantar Visualisasi Data dengan Seaborn

Latihan interaktif praktis

Cobalah latihan ini dengan menyelesaikan kode contoh berikut.

# Create line plot
g = sns.lineplot(x="model_year", y="mpg_mean", 
                 data=mpg_mean,
                 hue="origin")

# Add a title "Average MPG Over Time"


# Show plot
plt.show()

Edit dan Jalankan Kode

Latihan ini adalah bagian dari kursus

Pengantar Visualisasi Data dengan Seaborn

SkillTag.level.beginnerSkillTag.label

4.9+

Mulai Kursus Gratis

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: Mengubah gaya dan warna plot Exercise 2: Mengubah style dan palet Exercise 3: Mengubah skala Exercise 4: Menggunakan palet kustom Exercise 5: Menambahkan judul dan label: Bagian 1 Exercise 6: FacetGrid vs. AxesSubplot Exercise 7: Menambahkan judul ke objek FacetGrid Exercise 8: Menambahkan judul dan label: Bagian 2 Exercise 9: Menambahkan judul dan label sumbu

Latihan Saat Ini

Exercise 10: Memutar label x-tick Exercise 11: Menggabungkan semuanya Exercise 12: Box plot dengan subkelompok Exercise 13: Plot batang dengan subkelompok dan subplot Exercise 14: Kerja bagus! Apa selanjutnya?