Load multiple data files
It's perfectly fine to manually import multiple datasets. However, there will be times when you'd want to import a bunch of datasets without having to make multiple read_csv() calls.
You can use the glob library that is built into Python to look for files that match a pattern.
The library is called "glob" because "globbing" is the way patterns are specified in the Bash shell.
The glob() function returns a list of filenames that match a specified pattern.
You can then use a list comprehension to import multiple files into a list, and then you can extract the DataFrame of interest.
This is a part of the course
“Python for R Users”
Exercise instructions
- Obtain a list of all csv files in your current directory and assign it to
csv_files. - Write a list comprehension that reads in all the
csvfiles into a list,dfs. - Write a list comprehension that looks at the
.shapeof each DataFrame in the list.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
import glob
import pandas as pd
# Get a list of all the csv files
csv_files = glob.____('*.csv')
# List comprehension that loads of all the files
dfs = [pd.read_csv(____) for ____ in ____]
# List comprehension that looks at the shape of all DataFrames
print(____)This exercise is part of the course
Python for R Users
This course is for R users who want to get up to speed with Python!
As a final capstone, you will apply your Python skills on the NYC Flights 2013 dataset.
Exercise 1: NYC flights dataExercise 2: Load multiple data filesExercise 3: ExploreExercise 4: VisualizeExercise 5: Manipulating dataExercise 6: Recode datesExercise 7: Groupby aggregatesExercise 8: PlotsExercise 9: Dummy variablesExercise 10: Wrap-upWhat is DataCamp?
Learn the data skills you need online at your own pace—from non-coding essentials to data science and machine learning.