def main():
train_df = pd.read_csv('../data/processed/train_dropped.csv',
dtype=const.DTYPE)
question_df = pd.read_csv(const.INPUT_DATA_DIR / 'questions.csv')
train_features_df = get_features(train_df, question_df)
save_features(train_features_df, data_type='train')
def main():
train_df = pd.read_feather('../data/input/train_data.feather')
test_df = pd.read_feather('../data/input/test_data.feather')
train_features_df, test_features_df = get_features(train_df, test_df)
save_features(train_features_df, data_type='train')
save_features(test_features_df, data_type='test')
def main():
train_df = pd.read_csv('../data/input/train_concated.csv')
test_df = pd.read_csv('../data/input/test.csv')
train_features_df, test_features_df = get_features(train_df, test_df)
save_features(train_features_df, data_type='train')
save_features(test_features_df, data_type='test')
def main():
train_df = pd.read_csv(const.INPUT_DATA_DIR / 'train.csv',
dtype=const.DTYPE)
questions_df = pd.read_csv('../data/input/questions.csv')
q2p = dict(questions_df[['question_id', 'part']].values)
train_df['part'] = train_df['content_id'].map(q2p)
train_features_df = get_features(train_df)
save_features(train_features_df, data_type='train')
def main():
train_df = pd.read_csv('../data/processed/train_dropped.csv',
dtype=const.DTYPE)
question_df = pd.read_csv(const.INPUT_DATA_DIR / 'questions.csv',
dtype=const.DTYPE)
question_df.rename(columns={'question_id': 'content_id'}, inplace=True)
train_df = pd.merge(train_df, question_df, on='content_id', how='left')
train_features_df = get_features(train_df)
save_features(train_features_df, data_type='train')
def main():
train_df = pd.read_csv(const.INPUT_DATA_DIR / 'train.csv',
dtype=const.DTYPE)
question_df = pd.read_csv(const.INPUT_DATA_DIR / 'questions.csv')
question_df.rename(columns={'question_id': 'content_id'}, inplace=True)
train_df = pd.merge(train_df, question_df, on='content_id', how='left')
usecols = ['user_id', 'content_id', 'part', 'prior_question_elapsed_time']
train_features_df = get_features(train_df[usecols])
save_features(train_features_df, data_type='train')
def main():
train_df = dh.load('../data/input/train_concated.csv')
test_df = dh.load('../data/input/test.csv')
whole_df = pd.concat([train_df, test_df], axis=0, sort=False, ignore_index=True)
whole_features_df = get_features(whole_df)
train_features_df = whole_features_df.iloc[:len(train_df)]
test_features_df = whole_features_df.iloc[len(train_df):]
save_features(train_features_df, data_type='train')
save_features(test_features_df, data_type='test')
def main():
train_df = pd.read_csv('../data/processed/train_dropped.csv',
dtype=const.DTYPE)
lectures_df = pd.read_csv(const.INPUT_DATA_DIR / 'lectures.csv')
lectures_df.rename(columns={'lecture_id': 'content_id'}, inplace=True)
attempt_c = pd.read_feather('../features/dropped___attempt_c_train.feather'
)['dropped___attempt_c'].values
train_df['dropped___attempt_c'] = np.where(attempt_c <= 3, attempt_c, 4)
train_df = pd.merge(train_df, lectures_df, on='content_id', how='left')
train_features_df = get_features(train_df)
save_features(train_features_df, data_type='train')
def main():
train_df = dh.load('../data/input/train_concated.csv')
test_df = dh.load('../data/input/test.csv')
train2020_size_df = pd.read_csv('../data/input/train_image_size.csv')
train2019_size_df = pd.read_csv('../data/input/train_2019.csv', usecols=['image_name', 'height', 'width'])
train_size_df = pd.concat([
train2020_size_df,
train2019_size_df
], axis=0, sort=False, ignore_index=True)
test_size_df = pd.read_csv('../data/input/test_image_size.csv')
train_df = train_df.merge(train_size_df, on='image_name', how='left')
test_df = test_df.merge(test_size_df, on='image_name', how='left')
train_features_df, test_features_df = get_features(train_df, test_df)
save_features(train_features_df, data_type='train')
save_features(test_features_df, data_type='test')
def main():
train_df = pd.read_csv(const.INPUT_DATA_DIR / 'train.csv',
dtype=const.DTYPE)
train_features_df = get_features(train_df)
save_features(train_features_df, data_type='train')
def main():
train_df = pd.read_csv('../data/processed/train_dropped.csv',
dtype=const.DTYPE)
train_features_df = get_features(train_df)
save_features(train_features_df, data_type='train')
