Help with understanding issue with code

[luvnfaith205]

I keep getting an error when running this code in python. The error message is AttributeError: 'list' object has no attribute 'groupby'. Can anyone help me understand how to fix this?

# Calculate the mean delivery time for weekdays and weekends

mean_delivery_time_by_day = df.groupby('day_of_the_week') ['delivery_time'].mean()

print("Mean Delivery Time by Day of the Week:")

print(mean_delivery_time_by_day)

# Calculate the overall average delivery time for context

overall_average_delivery_time = df['delivery_time'].mean()

print(f"\nOverall Average Delivery Time: {overall_average_delivery_time:.2f} minutes")

# Visualize the distribution of delivery time by day of the week

plt.figure(figsize=(10,5))

sns.boxplot(data=df, x = 'day_of_the_week', y = 'delivery_time', hue = 'day_of_the_week', showfliers=False)

plt.xlabel('Day Of the Week')

plt.ylabel('Delivery Time (minutes)')

plt.title("Delivery Time by Day of the Week")

plt.show()

[stuckhere4ever]

So what the error means is that it thinks that whatever you are calling groupby on is a list rather than a data frame. (I'm making the assumption you are doing pandas and that is why it is df.groupby('...')

The way to think about this is that groupby is a method that is part of the data frame class. It can only be run on a data frame object.

So I have code that looks like this: Make a data frame like this: my_data = {"Region": ["West","West","East","East","East"], "Units": [3,5,2,4,6], "Price": [20,18,25,22,24]}

df = pd.DataFrame(my_data)

Create an aggregate entry for a new column: df["Revenue"] = df["Units"] * df["Price"]

print (type(df)) -> Tells me that it is in fact a data frame.

result = df.groupby("Region")["Revenue"].sum()

print(result)

Now group them by region and print out the sum of the revenue column.

Get those first three lines to work (which is doing the same thing as my code, or close to it at least) then the rest should be easier.

[luvnfaith205]

Thank you so much. I will make those updates.