2021-06-12 17:27:12 +02:00
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"""
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Download dataset between 10-20 mb,
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Split it into train/dev/test
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Return dataset info (length, max, min etc.)
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"""
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import string
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import pandas as pd
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from sklearn import preprocessing
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from sklearn.model_selection import train_test_split
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movies_data = pd.read_csv("imdb_movies.csv")
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# Drop rows with missing values
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movies_data.dropna(inplace=True)
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# Remove not interesting columns
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drop_columns = ["title_id", "certificate", "title", "plot"]
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drop_columns2 = [
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"original_title",
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"countries",
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"genres",
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"director",
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"cast",
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"release_date",
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]
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drop_columns = drop_columns + drop_columns2
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movies_data.drop(labels=drop_columns, axis=1, inplace=True)
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# Remove ',' from votes number and change type to int
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movies_data["votes_number"] = (movies_data["votes_number"].str.replace(",", "")).astype(
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int
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)
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# Normalize number values
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scaler = preprocessing.MinMaxScaler()
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movies_data[["votes_number", "year", "runtime"]] = scaler.fit_transform(
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movies_data[["votes_number", "year", "runtime"]]
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)
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# Split set to train/dev/test 6:2:2 ratio and save to .csv file
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train, dev = train_test_split(movies_data, train_size=0.6, test_size=0.4, shuffle=True)
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dev, test = train_test_split(dev, train_size=0.5, test_size=0.5, shuffle=True)
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train.to_csv("train.csv")
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dev.to_csv("dev.csv")
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test.to_csv("test.csv")
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