From 1918917126e8b8292b2a950ab5c52338e732bb09 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jakub=20Zar=C4=99ba?= Date: Tue, 23 May 2023 23:24:45 +0200 Subject: [PATCH] s --- prepare_data.py | 20 +- processed_data.csv | 48565 +++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 48573 insertions(+), 12 deletions(-) create mode 100644 processed_data.csv diff --git a/prepare_data.py b/prepare_data.py index f447418..36ddfef 100644 --- a/prepare_data.py +++ b/prepare_data.py @@ -1,20 +1,16 @@ import pandas as pd from sklearn.preprocessing import MinMaxScaler -def prepare_data(file_path): - data = pd.read_csv(file_path, sep=';') +data_path = 'data.csv' +processed_data_path = 'processed_data.csv' - data = pd.get_dummies(data, columns=['Sex', 'Medal']) - data = data.drop(columns=['Name', 'Team', 'NOC', 'Games', 'Year', 'Season', 'City', 'Sport', 'Event']) +data = pd.read_csv(data_path, sep=';') - data = data.fillna(0) - scaler = MinMaxScaler() - data = pd.DataFrame(scaler.fit_transform(data), columns=data.columns) +data = pd.get_dummies(data, columns=['Sex', 'Medal']) - return data +data = data.drop(columns=['Name', 'Team', 'NOC', 'Games', 'Year', 'Season', 'City', 'Sport', 'Event']) -if __name__ == "__main__": - file_path = 'olympics-124-years-datasettill-2020/Data.csv' - data = prepare_data(file_path) +scaler = MinMaxScaler() +data = pd.DataFrame(scaler.fit_transform(data), columns=data.columns) - data.to_csv('processed_data.csv', index=False) +data.to_csv(processed_data_path, index=False) diff --git a/processed_data.csv b/processed_data.csv new file mode 100644 index 0000000..8d3a397 --- /dev/null +++ b/processed_data.csv @@ -0,0 +1,48565 @@ +Id,Age,Sex_F,Sex_M,Medal_Bronze,Medal_Gold,Medal_Silver +0.0,0.21276595744680848,1.0,0.0,0.0,0.0,0.0 +3.6885261018549595e-06,0.21276595744680848,1.0,0.0,0.0,0.0,0.0 +7.377052203709921e-06,0.2978723404255319,1.0,0.0,0.0,0.0,0.0 +1.1065578305564879e-05,0.2978723404255319,1.0,0.0,0.0,0.0,0.0 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