diff --git a/py_scripts/digger.py b/py_scripts/digger.py
index 16b92a0..6be548f 100644
--- a/py_scripts/digger.py
+++ b/py_scripts/digger.py
@@ -1,6 +1,8 @@
 # Getting and combining data
 import pandas as pd
 import numpy as np
+from numpy import ndarray
+from scipy.stats import binned_statistic
 
 
 # Defining useful Functions to be used later
@@ -22,6 +24,7 @@ def write_joined_df(left, right, lsuf="new_key"):
 
 
 def slam_dunk(dataset, column, labels):
+    dataset[column] = dataset[column].fillna(0, inplace = True)
     min_value = dataset[column].min()
     max_value = dataset[column].max()
     print("min: ", min_value, " max: ", max_value)
@@ -32,4 +35,19 @@ def slam_dunk(dataset, column, labels):
     dataset[dunked_column] = pd.cut(
         dataset[column], bins=bins, labels=labels, include_lowest=True
     )
+
+    # filling column with means
+    dataset[column] = dataset[column].interpolate(method = "linear", limit_direction = "backward", limit = 1)
+
+    x_data = np.arange(0, len(dataset))
+    y_data = dataset[column]
+    x_bins, bin_edges, misc = binned_statistic(y_data, x_data, statistic='median', bins=len(labels))
+    bin_intervals = pd.IntervalIndex.from_arrays(bin_edges[:-1], bin_edges[1:])
+    dataset['PooShi'] = dataset[column].apply(lambda x: set_to_median(x, bin_intervals))
+
     return dataset
+
+def set_to_median(x, bin_intervals):
+    for interval in bin_intervals:
+        if x in interval:
+            return interval.mid
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