Tweetl 0.0.1

A package to do everything from getting tweets to pre-processing

Tweetl

By using tweetl, you can simplify the steps from getting tweets to pre-processing it. If you don't have twitter API key, you can get it here.

Installation

pip install tweetl

Usage

Getting Tweets

Create an instance of the 'GetTweet' Class.

import tweetl

# your api keys
consumer_api_key = "xxxxxxxxx"
consumer_api_secret_key = "xxxxxxxxx"
access_token = "xxxxxxxxx"
access_token_secret = "xxxxxxxxx"

# create an instance
tweet_getter = tweetl.GetTweet(
                    consumer_api_key,
                    consumer_api_secret_key, 
                    access_token, 
                    access_token_secret
                )

By target name

You can collect tweets of the target if you use 'get_tweets_target' method and set the target's name not inclueded '@'. Then it returns collected tweets as DataFrame type.

# get tweets of @Deepblue_ts
df_target = tweet_getter.get_tweets_target("Deepblue_ts")
df_target.head()

By any keyword

You can also get tweets about any keyword if you use 'get_tweets_keyword' method and set any one.

# get tweets about 'deep learning'
df_keyword = tweet_getter.get_tweets_keyword("deep learning")

Cleansing Tweets

Create an instance of the 'CleansingTweets' Class. And using 'cleansing_df' method, you can pre-processing tweets. You can select columns that you want to cleanse. The default is only text-colmn.

# make an instance
tweet_cleanser = tweetl.CleansingTweets()
cols = ["text", "user_description"]
df_clean = tweet_cleanser.cleansing_df(df_keyword, subset_cols=cols)

Author

deepblue

License

This software is released under the MIT License, see LICENSE.