Cursos

Data Analysis Python

1,800.00 +Iva

Duração: 4 dias
Próxima Data: 24/01/2022 a 27/01/2022
Área: Python
Certificação Associada: N/A
Local: Lisboa e Porto

*Curso disponível em Live Training

Quero inscrever-me
REF: PYDA Categorias: , Etiqueta:

Descrição

This course focuses on the extensive features of the Python data analysis workhorse library,Pandas,and its visualisation counterpart Matplotlib. It covers the reading,preparation and manipulation of tabular data from various sources and in various common formats. Most wrangling and manipulation processes are covered. Time series data processing and practical linear regression are also covered. For the programming environment we use JupyterLab on the Anaconda platform. Anaconda is one of the most,if not the most,popular data science platforms.

 

 

Destinatários

This course is designed for anyone with Python programming experience wanting to gain a solid foundation in Python’s data analysis libraries. It is a must for aspiring Data Analysts and Scientists. Existing Data Analysts wanting a systematic introduction to Python’s Data Analysis tools would also find the course very useful.

Programa

Module 1: INTRODUCTION TO DATAFRAMES

  • What is a DataFrame?
  • Loading DataFrames
  • Accessing contents
  • Useful functions
  • Adding and dropping columns and rows
  • Fitering and assigning data
  • Missing values and duplicates
  • Arithmetic basics
  • Applymap and apply

Module 2: COMBINING DATAFRAMES

  • Concatinate
  • Merge
  • Keys to merge on and suffixes for duplicate columns
  • Merge methods
  • Append
  • Join
  • Combine_first: For missing values

Module 3: RESHAPING DATAFRAMES

  • Unstacking and Stacking
  • Pivoting
  • Melting
  • Concatinating files from disk

Module 4: GROUPBY AND AGGREGATION: SPLIT-APPLY-COMBINE

  • Basic GroupBy
  • Hierarchical GroupBy
  • Group by function of Index
  • Aggregate by mapping on Index and Columns
  • Aggregate by user-defined functions
  • Aggregate using multiple functions
  • Aggregate using separate function for each column
  • Transfrom
  • Apply function
  • Pivoting with Aggregation

Module 5: PLOTTING WITH MATPLOTLIB

  • Pie chart
  • Bar chart
  • Histogram
  • Scatter plot
  • Line plot

Module 6: TIME SERIES DATA

  • Basic Concepts; Datetime,Timestamp,Timedelta,Timezones
  • Pandas to_date() fucntion
  • Date Range
  • What is time series data
  • Reading time series data
  • Missing Dates
  • Partial indexing,Slicing and Selecting
  • Resampling
  • Moving Window functions

Moduel 7: LINEAR REGRESSION

  • What is linear regression?
  • Simple Linear regression
  • Multiple Regression

 

Pré-requisitos

Delegates are expected to have Python programming experience. They should be able to effectively use Python containers (lists,tuples,dictionaries,and sets),construct loops and conditional statements,write functions and create and use classes and objects.

Outras datas

11/04/2022 15/04/2022

20/06/2022 a 24/06/2022