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(For Experimental and Practical purposes).Python is a powerful programming language widely used in data science due to its simplicity and versatility. It offers a rich ecosystem of libraries like Pandas, NumPy, and Matplotlib, which make data manipulation, analysis, and visualization efficient and intuitive.

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  1. i. Write a NumPy program to convert a list and tuple into arrays

ii. Write a NumPy program to convert the values of Centigrade degrees into Fahrenheit degrees and vice versa. Values have to be stored into a NumPy array.

i. Write a NumPy program to find the real and imaginary parts of an array of complex 2. numbers

ii. Write a NumPy program to convert a NumPy array into a csv file

  1. i. Write a NumPy program to perform the basic arithmetic operations

ii. Write a NumPy program to transpose an array

  1. i. Use NumPy. Create an array with 5 dimensions and verify that it has 5 dimensions.

ii. Using NumPy, Sort a boolean array

  1. i. Create your own simple Pandas DataFrame and print its values

ii. Create your own DataFrame from dict of narray/list

  1. i. Using Pandas, Create a DataFrame with a list of dictionaries, row indices, and column indices.

ii. Use index label to delete or drop rows from a Pandas DataFrame.

  1. Apply and explore various plotting functions on UCI data sets

  2. Compare the results of the Univariate and Bivariate analysis for the UCI diabetes data set

  3. Using Pandas library,

i.Load the iris.CSV file

ii. Convert it into the data frame and read it.

iii. Display records only with species "Iris-setosa".

  1. Use the diabetes data set from UCI, Perform Univariate analysis

  2. Use the diabetes data set from Pima Indians Diabetes, Perform Bivariate analysis.

  3. Perform Multiple Regression analysis on your own dataset (For example, Car dataset with information Company Name, Model, Volume, Weight, CO2) with more than one independent value to predict a value based on two or more variables.

ii. Using plt.contour(), plt.contourf(), plt.imshow(), plt.colorbar(), plt.clabel() functions visualize a contour plot

  1. Using the "concrete strength" dataset, explore relationships between two continuous

variables with Scatterplots

i. Draw a Scatter Plot for the following Pandas DataFrame with Team name and Rank

Points as x and y axis

["Australia", 2500],["Bangladesh", 1000],["England", 2000],['India", 3000],["Srilanka", 1500]

  1. Make a three-dimensional plot with randomly generate 50 data points for x, y, and z. Set

the point color as red, and size of the point as 50.

  1. How will you plot and visualize geographical data with the help of Basemap. State the Procedure for it with an example.

  2. Perform Reading data from text files, Excel and the web and exploring various commands for doing descriptive analytics on the Iris data set

  3. Perform Bivariate analysis using the pandas DataFrame that contains information about two variables: (1) Hours spent studying and (2) Exam score received by 20 different students:

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(For Experimental and Practical purposes).Python is a powerful programming language widely used in data science due to its simplicity and versatility. It offers a rich ecosystem of libraries like Pandas, NumPy, and Matplotlib, which make data manipulation, analysis, and visualization efficient and intuitive.

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