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Loading tweets into a DataFrame

Now it's time to import data into a pandas DataFrame so we can analyze tweets at scale.

We will work with a dataset of tweets which contain the hashtag '#rstats' or '#python'. This dataset is stored as a list of tweet JSON objects in data_science_json.

This course touches on a lot of concepts you may have forgotten, so if you ever need a quick refresher, download the pandas basics Cheat Sheet and keep it handy!

Be aware that this is real data from Twitter and as such there is always a risk for the presence of profanity or other offensive content (in this exercise, and any following exercises that also use real Twitter data).

This exercise is part of the course

Analyzing Social Media Data in Python

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Exercise instructions

  • Import pandas (remember, by convention we'll alias it as pd).
  • Flatten the data_science_json tweets with flatten_tweets() and store them in tweets.
  • Create a DataFrame from tweets using pd.DataFrame().
  • Print out the text from the first 5 tweets.

Hands-on interactive exercise

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

# Import pandas
import ____ as ____

# Flatten the tweets and store in `tweets`
tweets = ____(____)

# Create a DataFrame from `tweets`
ds_tweets = ____(____)

# Print out the first 5 tweets from this dataset
print(ds_tweets[____].values[0:5])
Edit and Run Code