c6f886148450abd45db031461210de805579c75c,demo_semiotic.py,,,#,3

Before Change

import scattertext as st

movie_df = st.SampleCorpora.RottenTomatoes.get_data()
movie_df.category = movie_df.category.apply \
	(lambda x: {"rotten": "Negative", "fresh": "Positive", "plot": "Plot"}[x])
corpus = st.CorpusFromPandas(
	movie_df,
	category_col="category",

After Change

	category_b="rotten",
	neutral_categories=["plot"],
	scorer=st.RankDifference(),
	labels={"not_a_and_not_b": "Plot Descriptions",
	        "a_and_b": "Reviews",
	        "a_and_not_b": "Positive",
	        "b_and_not_a": "Negative",
	        "a":"",
	        "b":"",
	        "not_a":"",
	        "not_b":""}
)

html = st.produce_semiotic_square_explorer(semiotic_square,
                                           category_name="fresh",

Instances