Calculate Percentile & Decile in Python – List & DataFrame Column (4 Examples)
In this tutorial, I’ll illustrate how to get the percentiles and deciles in the Python programming language.
Example 1: Calculating the Deciles of a List Object
my_lt = [10, 6, 2, 2, 15, 20, 3, 7, 4] # Constructing a list in Python print(my_lt) # [10, 6, 2, 2, 15, 20, 3, 7, 4] |
my_lt = [10, 6, 2, 2, 15, 20, 3, 7, 4] # Constructing a list in Python print(my_lt) # [10, 6, 2, 2, 15, 20, 3, 7, 4]
import numpy as np # Import NumPy library |
import numpy as np # Import NumPy library
print(np.quantile(my_lt, np.arange(0.1, 1, 0.1))) # Computing the deciles of a list # [ 2. 2.6 3.4 4.4 6. 6.8 8.8 12. 16. ] |
print(np.quantile(my_lt, np.arange(0.1, 1, 0.1))) # Computing the deciles of a list # [ 2. 2.6 3.4 4.4 6. 6.8 8.8 12. 16. ]
Example 2: Calculating the Percentiles of a List Object
print(np.quantile(my_lt, np.arange(0.01, 1, 0.01))) # Computing the percentiles of a list # [ 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. # 2.04 2.12 2.2 2.28 2.36 2.44 2.52 2.6 2.68 2.76 2.84 2.92 # 3. 3.08 3.16 3.24 3.32 3.4 3.48 3.56 3.64 3.72 3.8 3.88 # 3.96 4.08 4.24 4.4 4.56 4.72 4.88 5.04 5.2 5.36 5.52 5.68 # 5.84 6. 6.08 6.16 6.24 6.32 6.4 6.48 6.56 6.64 6.72 6.8 # 6.88 6.96 7.12 7.36 7.6 7.84 8.08 8.32 8.56 8.8 9.04 9.28 # 9.52 9.76 10. 10.4 10.8 11.2 11.6 12. 12.4 12.8 13.2 13.6 # 14. 14.4 14.8 15.2 15.6 16. 16.4 16.8 17.2 17.6 18. 18.4 # 18.8 19.2 19.6 ] |
print(np.quantile(my_lt, np.arange(0.01, 1, 0.01))) # Computing the percentiles of a list # [ 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. # 2.04 2.12 2.2 2.28 2.36 2.44 2.52 2.6 2.68 2.76 2.84 2.92 # 3. 3.08 3.16 3.24 3.32 3.4 3.48 3.56 3.64 3.72 3.8 3.88 # 3.96 4.08 4.24 4.4 4.56 4.72 4.88 5.04 5.2 5.36 5.52 5.68 # 5.84 6. 6.08 6.16 6.24 6.32 6.4 6.48 6.56 6.64 6.72 6.8 # 6.88 6.96 7.12 7.36 7.6 7.84 8.08 8.32 8.56 8.8 9.04 9.28 # 9.52 9.76 10. 10.4 10.8 11.2 11.6 12. 12.4 12.8 13.2 13.6 # 14. 14.4 14.8 15.2 15.6 16. 16.4 16.8 17.2 17.6 18. 18.4 # 18.8 19.2 19.6 ]
Example 3: Calculating the Deciles of the Columns in a pandas DataFrame
import pandas as pd # Import pandas library |
import pandas as pd # Import pandas library
my_df = pd.DataFrame({'A':range(100, 108), # Constructing a pandas DataFrame 'B':[6, 1, 8, 7, 3, 5, 5, 9], 'C':range(1, 9)}) print(my_df) # A B C # 0 100 6 1 # 1 101 1 2 # 2 102 8 3 # 3 103 7 4 # 4 104 3 5 # 5 105 5 6 # 6 106 5 7 # 7 107 9 8 |
my_df = pd.DataFrame({'A':range(100, 108), # Constructing a pandas DataFrame 'B':[6, 1, 8, 7, 3, 5, 5, 9], 'C':range(1, 9)}) print(my_df) # A B C # 0 100 6 1 # 1 101 1 2 # 2 102 8 3 # 3 103 7 4 # 4 104 3 5 # 5 105 5 6 # 6 106 5 7 # 7 107 9 8
print(my_df.quantile(np.arange(0.1, 1, 0.1))) # Computing the deciles of all columns # A B C # 0.1 100.7 2.4 1.7 # 0.2 101.4 3.8 2.4 # 0.3 102.1 5.0 3.1 # 0.4 102.8 5.0 3.8 # 0.5 103.5 5.5 4.5 # 0.6 104.2 6.2 5.2 # 0.7 104.9 6.9 5.9 # 0.8 105.6 7.6 6.6 # 0.9 106.3 8.3 7.3 |
print(my_df.quantile(np.arange(0.1, 1, 0.1))) # Computing the deciles of all columns # A B C # 0.1 100.7 2.4 1.7 # 0.2 101.4 3.8 2.4 # 0.3 102.1 5.0 3.1 # 0.4 102.8 5.0 3.8 # 0.5 103.5 5.5 4.5 # 0.6 104.2 6.2 5.2 # 0.7 104.9 6.9 5.9 # 0.8 105.6 7.6 6.6 # 0.9 106.3 8.3 7.3
Example 4: Calculating the Percentiles of the Columns in a pandas DataFrame
print(my_df.quantile(np.arange(0.01, 1, 0.01))) # Computing the percentiles of all columns # A B C # 0.01 100.07 1.14 1.07 # 0.02 100.14 1.28 1.14 # 0.03 100.21 1.42 1.21 # 0.04 100.28 1.56 1.28 # 0.05 100.35 1.70 1.35 # ... ... ... # 0.95 106.65 8.65 7.65 # 0.96 106.72 8.72 7.72 # 0.97 106.79 8.79 7.79 # 0.98 106.86 8.86 7.86 # 0.99 106.93 8.93 7.93 # # [99 rows x 3 columns] |
print(my_df.quantile(np.arange(0.01, 1, 0.01))) # Computing the percentiles of all columns # A B C # 0.01 100.07 1.14 1.07 # 0.02 100.14 1.28 1.14 # 0.03 100.21 1.42 1.21 # 0.04 100.28 1.56 1.28 # 0.05 100.35 1.70 1.35 # ... ... ... # 0.95 106.65 8.65 7.65 # 0.96 106.72 8.72 7.72 # 0.97 106.79 8.79 7.79 # 0.98 106.86 8.86 7.86 # 0.99 106.93 8.93 7.93 # # [99 rows x 3 columns]