An animated phrase cloud shows absolute frequencies of n-grams (contiguous sequences of textual content pattern objects) over time as a sequence of photographs in a video file. It offers larger significance to phrases that seem extra ceaselessly in a supply textual content. The larger and bolder the n-gram shows, the extra ceaselessly it seems within the textual content. It builds on the intuitive logic of traditional phrase clouds and provides a time perspective to the visualization.
As many textual content datasets are collected lately as textual content observations over a number of intervals, there’s a specific problem to visualise the modifications within the knowledge over time. As an alternative of creating abstract tables or graphs for a lot of completely different intervals, let’s put together an MP4 video that tells the story, attracts the viewers, and provides a “wow” impact to the presentation.
This text will describe the era of animated phrase clouds from textual content knowledge in Python. Listed below are some distinctive options of the AnimatedWordCloud library:
- Offers n-gram frequency visualization of all Latin-alphabet languages
- Cleans textual content dataset from punctuation, numbers, and stopwords included within the NLTK lists of stopwords
- Generates yearly or month-to-month n-gram frequencies.
