Python

Introduction and Data preparation Please follow the folloing links regarding data preparation and previous posts to follow along - For Data Preparation - Part 0 - Plotting Using Seaborn - Data …

Import Preliminaries and datasets import pandas as pd import seaborn as sns import matplotlib.pyplot as plt import matplotlib.pylab as plb import warnings warnings.filterwarnings('ignore') test_scores = …

Preliminaries Distance Matrics L2 Norm L1 Norm Nearest Neighbor Using L2 Distance Using L1 Distance Predictions Errors Confusion Matrix Using Pandas From Scratch Preliminaries import numpy as np # Load data set and code …

Try and Except Handle Exceptions Exceptions Attributes Handling Multiple Exceptions Else Finally Try and Except Handle Exceptions The following statement will throw an error as string can’t be parsed into …

Return in Function Scoping in Function Access global variable in function context Declare a local variable within in a function Declare local variable with same name as in global Using Global Keyword *args and **kwargs …

Continue vs Break Continue print("The loop will skip the value when value of i is 2 and restart from next value of i - ") for i in range(0,4): if i == 2: continue else: print(i+100) Output: The loop will skip …

Importing Packages and Datasets import pandas as pd import numpy as np start_date = ['2019-06-03', '2019-06-13', '2018-11-05', '2019-05-31', '2019-06-01', '2019-09-01'] …

Importing Packages and Datasets import pandas as pd start_date = ['2019-06-03', '2019-06-13', '2019-10-01', '2019-09-01'] end_date = ['2019-08-31', '2019-06-21', …

Importing Packages and Datasets import pandas as pd import numpy as np data = pd.DataFrame(np.random.rand(4, 3)*100, columns=['Physics','Çhemistry','Maths'], index = ['Student 1', …

Filtering a dataframe can be achieved in multiple ways using pandas. There are times when you simply need to update a column based on a condition which is true or vice-versa. In pandas dataframe there are some inbuilt …