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83 lines
2.5 KiB
Python
83 lines
2.5 KiB
Python
# Author - Kristiāns Francis Cagulis
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# Date - 19.01.2022
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# Title - Classwork
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import pandas as pd
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from word2number import w2n
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def main():
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data = pd.read_csv("auto_imports_mainits.csv")
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# summary = data["normalized-losses"].notnull() # returns boolean
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# print(data[summary], "\n") # "normalized-losses" is not empty
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# print(data[~summary]) # inverts all the bits
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# print(len(data[~summary]))
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data_copy = data.copy()
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# Delete rows with empty spots
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# print(f"Before erasing: {data_copy.shape}")
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# print(f"After erasing: {data_copy.dropna().shape}")
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# Delete column
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# print(f"Before erasing: {data_copy.shape}")
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del data_copy["normalized-losses"]
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# print(f"After erasing: {data_copy.shape}")
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# print(f"Blank spots: {data_copy.isnull().any().sum()}")
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# data_copy2 = data_copy.copy()
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# print(data_copy2.head())
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# data_copy2.drop(data_copy2.columns[[0, 1]], axis=1, inplace=True)
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# print(data_copy2.head())
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dislike = ["N/A", "NA", "--"]
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data_copy3 = pd.read_csv("auto_imports_mainits.csv", na_values=dislike)
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# Mean
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# print(data_copy3.iloc[52], "\n")
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# mean = data_copy3["bore"].mean()
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# data_copy3["bore"].fillna(mean, inplace=True)
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# print(data_copy3.iloc[52])
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# Median
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# print(data_copy3.iloc[53], "\n")
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# median = data_copy3["bore"].median()
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# data_copy3["bore"].fillna(median, inplace=True)
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# print(data_copy3.iloc[53])
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# Mode
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# print(data_copy3.iloc[60], "\n")
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# mode = data_copy3["bore"].mode()
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# data_copy3["bore"].fillna(mode, inplace=True)
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# print(data_copy3.iloc[60])
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# print(data_copy3.dtypes)
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# data_copy3["curb-weight"] = pd.to_numeric(data_copy3["curb-weight"], errors='coerce')
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# data_copy3["curb-weight"] = data_copy3["curb-weight"].astype("float64")
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# print(data_copy3.dtypes)
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# Replaces word written numbers to intigers
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columns = ["num-of-doors", "num-of-cylinders"]
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for column in columns:
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for value in data_copy3[column]:
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try:
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data_copy3 = data_copy3.replace(
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to_replace=value, value=w2n.word_to_num(value))
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print(type(w2n.word_to_num(value)))
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except:
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pass
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print(data_copy3[["num-of-doors", "num-of-cylinders"]])
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# Leaves only columns that contain numbers
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data_copy4 = data_copy3.copy()
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for column in data_copy4:
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if isinstance(data_copy4[column][0], str):
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del data_copy4[column]
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print(data_copy4)
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if __name__ == '__main__':
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main()
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