DATA SCIENCE WITH PYTHON TRAINING IN BANGALORE

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• Installing Python Anaconda distribution
• Python native Data Types
• Math & Comparision Operators
• Conditional Statement
• Loops
• Lists, Tuples, Strings, Dictionaries, Sets
• Functions
• Exception Handling

• Importing Numpy
• Numpy overview
• Numpy Array creation and basic operations
• Numpy Universal functions
• Selecting and retrieving Data
• Data Slicing
• Iterating Numpy Data
• Shape Manupilation
• Stacking and Splitting Arrays
• Copies and Views : no copy, shallow copy , deep copy

• Importing Pandas
• Pandas overview
• Object Creation : Series Object , DataFrame Object
• View Data
• Selecting data by Label and Position
• Data Slicing
• Boolean Indexing
• Setting Data

• Applying functions to data
• Histogramming
• String Methods
• Merge Data : Concat, Join and Append
• Grouping & Aggregation
• Reshaping
• Analysing Data for missing values
• Filling missing values: fill with constant, forward filling, mean
• Removing Duplicates
• Transforming Data

• Droping Data
• Sorting Data
• Pivot Tables
• Time Series
• Categoricals
• Ploting Data
• Import and Export Data

• Descriptive Statistics : Sum, Mean, Median, Variance, Standard Deviation
• Summarizing Categorical Data
• Plotting with Pandas
• Correlation : Continuous and Categorical ( Pearson Corr Coff)
• Chi-Square test for independence
• Normalizing & Standarding

• • Importing MatPlotLib & Seaborn Libraries
  • Creating basic chart : Line Chart, Bar Charts and Pie Charts
  • Ploting from Pandas object
  • Saving a plot
  • Object Oriented Plotting : Setting axes limits and ticks
  • Multiple Plots
  • Plot Formatting : Custom Lines, Markers, Labels, Annotations, Colors
  • Satistical Plots with Seaborn