Advanced Programming for Analytics

Importing numpy library, creating numpy arrays, indexing and slicing arrays,performing numerical operations on arrays, converting data frames to numpy arrays, creating multidimensional arrays, numpy data type object (dtype), concatenating, reshaping and flattening multidimesional arrays, repeating patterns uisng “tile” method. Reading and writing data files using functions: savetxt, loadtxt, tofile ,fromfile,save ,load, genfromtxt

Importing pandas library, Usingseries and Data Frames, indexing, Grouping, aggregating, MergingdataFrames, dealing with missing values using dropna method ,filtering or filling in missing data, creating dataframes from dictionaries or nested dictionaries, accessing and changing values of data frame using loc,at,replace methods,reading and writing csv,excel files

Importing Visualisation libraries: Matplotlib: format parameter of pylpot.plot ,subplots method, checking and defining ranges of axes, using linspace and linstyle, specifying legend, title Style, creating Scatter plots ,Bar charts, histogram, Stack charts, Saving plots. Importing seaborn library:Style functions, color palettes, Distribution plots ,categorical plots

Creating databases using MYSQL and SQLite: Importing the modules, creating connection object, creating tables, performing database operations (insert, update, delete),closing connection. .GUI programming with Tkinter: widgets(label, text, radio button, check boxes, entry, canvas, dialogs, menus)

Implementing Machine Learning with scikit-learn: loading and Visualizing datasets (sample sklearn datasets), splitting train and test data. Implementing deep learning with tensorflow and keras

*Case studies related to entire topics are to be taught.