AIGHT DONE FR THIS TIME
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@@ -116,3 +116,4 @@ sample_rows = gammas.iloc[chosen_idx]
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print(sample_rows.head())
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print(sample_rows.head())
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scout.dissimilarity(sample_rows)
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scout.dissimilarity(sample_rows)
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scout.similarity(sample_rows)
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@@ -52,7 +52,7 @@ def dissimilarity(row_arr):
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row_arr = row_arr.select_dtypes(include = np.number)
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row_arr = row_arr.select_dtypes(include = np.number)
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row_arr = row_arr.drop('Rank', axis = 1)
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row_arr = row_arr.drop('Rank', axis = 1)
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print(" | Entry 1 | Entry 2 | Entry 3 | Entry 4 | Entry 5 |")
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print(" Dissim | Entry 1 | Entry 2 | Entry 3 | Entry 4 | Entry 5 |")
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for i in range(len(row_arr)):
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for i in range(len(row_arr)):
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print("Entry " , i + 1, " | ", end = "")
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print("Entry " , i + 1, " | ", end = "")
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for j in range(len(row_arr)):
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for j in range(len(row_arr)):
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@@ -60,6 +60,18 @@ def dissimilarity(row_arr):
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print(" {:#.6g} |".format(eucDist), end = "")
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print(" {:#.6g} |".format(eucDist), end = "")
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print("\n")
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print("\n")
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def similarity(row_arr):
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row_arr = row_arr.select_dtypes(include = np.number)
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row_arr = row_arr.drop('Rank', axis = 1)
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print("Similarity| Entry 1 | Entry 2 | Entry 3 | Entry 4 | Entry 5 |")
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for i in range(len(row_arr)):
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print("Entry ", i + 1, " | ", end = "")
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for j in range(len(row_arr)):
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sim = 1 - distance.cosine(row_arr.iloc[i], row_arr.iloc[j])
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print(" {:#.6g} |".format(sim), end = "")
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print("\n")
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def scaling_range(datashitter, col):
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def scaling_range(datashitter, col):
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nonnull = datashitter[col].isna()
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nonnull = datashitter[col].isna()
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minmax_scaler = preprocessing.MinMaxScaler()
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minmax_scaler = preprocessing.MinMaxScaler()
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