Ekstrak sebuah fungsi

Saat mengembangkan model untuk memprediksi kelulusan perguruan tinggi, Anda menulis kode di bawah ini untuk mendapatkan z-score dari IPK tahunan mahasiswa (z-score menunjukkan simpangan baku dari nilai rata-rata). Sekarang Anda siap mengubahnya menjadi sistem siap produksi, sehingga Anda perlu menangani pengulangan kode. Menulis fungsi untuk menghitung z-score akan membuatnya lebih baik.

# Standarkan IPK untuk setiap tahun
df['y1_z'] = (df.y1_gpa - df.y1_gpa.mean()) / df.y1_gpa.std()
df['y2_z'] = (df.y2_gpa - df.y2_gpa.mean()) / df.y2_gpa.std()
df['y3_z'] = (df.y3_gpa - df.y3_gpa.mean()) / df.y3_gpa.std()
df['y4_z'] = (df.y4_gpa - df.y4_gpa.mean()) / df.y4_gpa.std()

Catatan: df adalah pandas DataFrame di mana setiap baris merepresentasikan seorang mahasiswa dengan 4 kolom IPK tahunan: y1_gpa, y2_gpa, y3_gpa, y4_gpa.

Latihan ini adalah bagian dari kursus

Menulis Function di Python

Petunjuk latihan

Lengkapi fungsi agar mengembalikan z-score dari sebuah kolom.
Gunakan fungsi tersebut untuk menghitung z-score tiap tahun (df['y1_z'], df['y2_z'], dll.) dari skor IPK mentah (df.y1_gpa, df.y2_gpa, dll.).

Latihan interaktif praktis

Cobalah latihan ini dengan menyelesaikan kode contoh berikut.

def standardize(column):
  """Standardize the values in a column.

  Args:
    column (pandas Series): The data to standardize.

  Returns:
    pandas Series: the values as z-scores
  """
  # Finish the function so that it returns the z-scores
  z_score = (____ - ____.____()) / ____.____()
  return z_score

# Use the standardize() function to calculate the z-scores
df['y1_z'] = ____
df['y2_z'] = ____
df['y3_z'] = ____
df['y4_z'] = ____

Edit dan Jalankan Kode

Latihan ini adalah bagian dari kursus

Menulis Function di Python

SkillTag.level.intermediateSkillTag.label

4.8+

Mulai Kursus Gratis

The goal of this course is to transform you into a Python expert, and so the first chapter starts off with best practices when writing functions. You'll cover docstrings and why they matter and how to know when you need to turn a chunk of code into a function. You will also learn the details of how Python passes arguments to functions, as well as some common gotchas that can cause debugging headaches when calling functions.

Exercise 1: Docstring Exercise 2: Menyusun sebuah docstring Exercise 3: Mengambil docstring Exercise 4: Docstring jadi penyelamat!Exercise 5: DRY dan "Lakukan Satu Hal"Exercise 6: Ekstrak sebuah fungsi

Latihan Saat Ini

Exercise 7: Membagi sebuah fungsi Exercise 8: Pass by assignment Exercise 9: Mutable atau immutable?Exercise 10: Praktik terbaik untuk argumen default

If you've ever seen the "with" keyword in Python and wondered what its deal was, then this is the chapter for you! Context managers are a convenient way to provide connections in Python and guarantee that those connections get cleaned up when you are done using them. This chapter will show you how to use context managers, as well as how to write your own.

Exercise 1: Using context managers Exercise 2: The number of cats Exercise 3: The speed of cats Exercise 4: Writing context managers Exercise 5: The timer() context manager Exercise 6: A read-only open() context manager Exercise 7: Advanced topics Exercise 8: Context manager use cases Exercise 9: Scraping the NASDAQ Exercise 10: Changing the working directory

Decorators are an extremely powerful concept in Python. They allow you to modify the behavior of a function without changing the code of the function itself. This chapter will lay the foundational concepts needed to thoroughly understand decorators (functions as objects, scope, and closures), and give you a good introduction into how decorators are used and defined. This deep dive into Python internals will set you up to be a superstar Pythonista.

Exercise 1: Functions are objects Exercise 2: Building a command line data app Exercise 3: Reviewing your co-worker's code Exercise 4: Returning functions for a math game Exercise 5: Scope Exercise 6: Understanding scope Exercise 7: Modifying variables outside local scope Exercise 8: Closures Exercise 9: Checking for closure Exercise 10: Closures keep your values safe Exercise 11: Decorators Exercise 12: Using decorator syntax Exercise 13: Defining a decorator

Now that you understand how decorators work under the hood, this chapter gives you a bunch of real-world examples of when and how you would write decorators in your own code. You will also learn advanced decorator concepts like how to preserve the metadata of your decorated functions and how to write decorators that take arguments.

Exercise 1: Real-world examples Exercise 2: Print the return type Exercise 3: Counter Exercise 4: Decorators and metadata Exercise 5: Preserving docstrings when decorating functions Exercise 6: Measuring decorator overhead Exercise 7: Decorators that take arguments Exercise 8: Run_n_times()Exercise 9: HTML Generator Exercise 10: Timeout(): a real world example Exercise 11: Tag your functions Exercise 12: Check the return type Exercise 13: Great job!