Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Leer How Much Do We Earn | Becoming an Analyst
Introduction to Python for Data Analysis
course content

Cursusinhoud

Introduction to Python for Data Analysis

Introduction to Python for Data Analysis

1. Introduction to Python 1/2
2. Introduction to Python 2/2
3. Explore Dataset
4. Becoming an Analyst

book
How Much Do We Earn

You may recognize the column 'money_spent' that corresponds to the amount of money the user spent and gained. In this chapter, we will find if there is any dependence between the day of the week and the amount of money we have!

But firstly, recall some functions:

Group Data:

12
df = df[['columns which we group']] .groupby(['columns on which we group'])
copy

Visualization:

1234
sns.barplot(df = DataFrame, x = 'column for x-axis', y = 'column for y-axis') plt.show()
copy
Taak

Swipe to start coding

  1. Group data:
  • Extract only columns 'day', 'money_spent' from the df DataFrame.
  • Group by the column 'day'.
  • Apply .mean() function to grouped df.
  • Apply .reset_index() function.
  1. Create a barplot:
  • Use df as the first argument.
  • Use column 'day' for x-axis.
  • Use the column 'money_spent' for the y-axis.
  1. Output barplot.

Oplossing

Switch to desktopSchakel over naar desktop voor praktijkervaringGa verder vanaf waar je bent met een van de onderstaande opties
Was alles duidelijk?

Hoe kunnen we het verbeteren?

Bedankt voor je feedback!

Sectie 4. Hoofdstuk 8
toggle bottom row

book
How Much Do We Earn

You may recognize the column 'money_spent' that corresponds to the amount of money the user spent and gained. In this chapter, we will find if there is any dependence between the day of the week and the amount of money we have!

But firstly, recall some functions:

Group Data:

12
df = df[['columns which we group']] .groupby(['columns on which we group'])
copy

Visualization:

1234
sns.barplot(df = DataFrame, x = 'column for x-axis', y = 'column for y-axis') plt.show()
copy
Taak

Swipe to start coding

  1. Group data:
  • Extract only columns 'day', 'money_spent' from the df DataFrame.
  • Group by the column 'day'.
  • Apply .mean() function to grouped df.
  • Apply .reset_index() function.
  1. Create a barplot:
  • Use df as the first argument.
  • Use column 'day' for x-axis.
  • Use the column 'money_spent' for the y-axis.
  1. Output barplot.

Oplossing

Switch to desktopSchakel over naar desktop voor praktijkervaringGa verder vanaf waar je bent met een van de onderstaande opties
Was alles duidelijk?

Hoe kunnen we het verbeteren?

Bedankt voor je feedback!

Sectie 4. Hoofdstuk 8
Switch to desktopSchakel over naar desktop voor praktijkervaringGa verder vanaf waar je bent met een van de onderstaande opties
Onze excuses dat er iets mis is gegaan. Wat is er gebeurd?
some-alt