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:
12df = df[['columns which we group']] .groupby(['columns on which we group'])
Visualization:
1234sns.barplot(df = DataFrame, x = 'column for x-axis', y = 'column for y-axis') plt.show()
Swipe to start coding
- Group data:
- Extract only columns
'day', 'money_spent'from thedfDataFrame. - Group by the column
'day'. - Apply
.mean()function to groupeddf. - Apply
.reset_index()function.
- Create a barplot:
- Use
dfas the first argument. - Use column
'day'for x-axis. - Use the column
'money_spent'for the y-axis.
- Output barplot.
Lösning
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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:
12df = df[['columns which we group']] .groupby(['columns on which we group'])
Visualization:
1234sns.barplot(df = DataFrame, x = 'column for x-axis', y = 'column for y-axis') plt.show()
Swipe to start coding
- Group data:
- Extract only columns
'day', 'money_spent'from thedfDataFrame. - Group by the column
'day'. - Apply
.mean()function to groupeddf. - Apply
.reset_index()function.
- Create a barplot:
- Use
dfas the first argument. - Use column
'day'for x-axis. - Use the column
'money_spent'for the y-axis.
- Output barplot.
Lösning
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Awesome!
Completion rate improved to 2.08single
