def norm_pca3(x, y):
if data_loading.dataframe_already_exists(constants.OUTPUT_DATA_PROC_PATH,
DATA_PCA3):
return None
y = y.reset_index(drop=True)
norm_df = _normalize(x)
pca_df = _pca(norm_df, 3)
joined_df = pd.concat((norm_df, pca_df, y),
axis=1)
assert norm_df.shape[0] == pca_df.shape[0] == joined_df.shape[0]
data_loading.save_data(joined_df, constants.OUTPUT_DATA_PROC_PATH,
DATA_PCA3)
def norm_tsne2(x, y):
if data_loading.dataframe_already_exists(constants.OUTPUT_DATA_PROC_PATH,
DATA_TSNE2):
return None
y = y.reset_index(drop=True)
norm_df = _normalize(x)
tsne_df = _tsne(norm_df, 2)
joined_df = pd.concat((norm_df, tsne_df, y),
axis=1)
assert norm_df.shape[0] == tsne_df.shape[0] == joined_df.shape[0]
data_loading.save_data(joined_df, constants.OUTPUT_DATA_PROC_PATH,
DATA_TSNE2)
def no_transform(dataframe):
if data_loading.dataframe_already_exists(constants.OUTPUT_DATA_PROC_PATH,
DATA_VANILLA):
return None
data_loading.save_data(dataframe, constants.OUTPUT_DATA_PROC_PATH,
DATA_VANILLA)