rewrite function handle_normalization
continuous-integration/drone/push Build is passing Details

pull/22/head
remrem 10 months ago
parent b5feac89cb
commit 0910dfae21

@ -20,11 +20,6 @@ def csv_check(df):
print("-"*12) print("-"*12)
print(df[col].unique()) print(df[col].unique())
def do_for_columns(df):
for col_name in df:
df[col_name] = function(df[col_name])
def csv_norm_min_max(df, col): def csv_norm_min_max(df, col):
max = df[col].max() max = df[col].max()
min = df[col].min() min = df[col].min()
@ -50,17 +45,13 @@ def csv_robust_normalize(df, col):
return normalized_column return normalized_column
def handle_normalization(df, norm_method): def handle_normalization(df, norm_method):
if norm_method == "min-max": for col_name in df:
for col_name in df: if norm_method == "min-max":
df[col_name] = csv_norm_min_max(df, col_name) df[col_name] = csv_norm_min_max(df, col_name)
return df elif norm_method == "z-score":
elif norm_method == "z-score":
for col_name in df:
df[col_name] = csv_standardisation_Z(df, col_name) df[col_name] = csv_standardisation_Z(df, col_name)
return df elif norm_method == "robust":
elif norm_method == "robust":
for col_name in df:
df[col_name] = csv_robust_normalize(df, col_name) df[col_name] = csv_robust_normalize(df, col_name)
return df else:
else: raise ValueError("Unknown method")
raise ValueError("Unknown method") return df

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