Combine daily requests for February

It's been a month since Sam last ran the report script, and it's time for her to make a new report for February.

She wants to upload new reports for February and update the file listing, expanding on the work she completed during the last video lesson:

Directory listing screenshot

She has already created the boto3 S3 client and stored in the s3 variable. She stored the contents of her objects in request_files.

You will help Sam aggregate the requests from February by downloading files from the gid-requests bucket and concatenating them into one DataFrame!

This exercise is part of the course

Introduction to AWS Boto in Python

View Course

Exercise instructions

Load each object from s3.
Read it into pandas and append it to df_list.
Concatenate all DataFrames in df_list.
Preview the DataFrame.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

df_list = [] 

# Load each object from s3
for file in request_files:
    s3_day_reqs = s3.____(Bucket='gid-requests', 
                                Key=file['Key'])
    # Read the DataFrame into pandas, append it to the list
    day_reqs = pd.read_csv(s3_day_reqs['____'])
    df_list.append(day_reqs)

# Concatenate all the DataFrames in the list
all_reqs = pd.____(df_list)

# Preview the DataFrame
all_reqs.head()

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