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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).

Cet exercice fait partie du cours

<cours>Analyzing Social Media Data in Python</cours>
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Instructions de l’exercice

  • 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.

Exercice interactif pratique

Essayez cet exercice en complétant ce code d’exemple.

# 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])
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