Mask for filters on train feature set

mask_train.py

filters = {
  'field_1': <threshold value for the field1>,
  'field_2': <threshold value for the field2>,
  }

# creates a matrix of True's
mask = np.ones(features.shape[0], dtype=bool)

for field, threshold_value in filters.items():
    # updates the matrix with
    # applied and accumulated conditions
    mask &= data[field] < threshold_value

    
    
# ---- USAGE ----
features = pd.DataFrame({'x': [1, 2, 3, 4, 5, 6], 'y': [3, 4, 5, 6, 7, 8]})
label = pd.DataFrame({'z': [1, 0, 1, 1, 0, 0]})

filters = {'x': 3, 'y': 6}
mask = np.ones(features.shape[0], dtype=bool)
for field, threshold_value in filters.items():
    # updates the matrix with
    # applied and accumulated conditions
    mask &= features[field] < threshold_value

# filtered train set
features = features.loc[mask]
label = label.loc[mask]

features
# x  y
# 0  1  3
# 1  2  4

label
#    z
# 0  1
# 1  0