Python – Advanced

Analysis
Data Science
Open Source
On-site courses
Face-to-face
Remote/Virtual
English
French

Objectives

  • Deepen the tools to represent and manipulate complex data, effectively use the pandas library, import data sources (CSV, JSON, XML, SQL), perform a simple or multiple linear regression model with the statmodels library, perfect your knowledge of matplotlib and know how to use seaborn or plotly..
  • At the end of this training, the participant should be able to import or even merge structured or unstructured data sources, apply advanced processing on quantitative and qualitative data and build elaborate static or dynamic graphs.

Prerequisites

Prerequisites

  • None

Pedagogical and technical material and resources

  • Dedicated digital training platform (LMS).
  • Sessions with the trainer, training material in digital format, balance between theoretical and practice, concrete cases.

Assessment

  • Practical application and exercises

Results & skills expected at the end of the training

  • At the end of this training, the participant should be able to import or even merge structured or unstructured data sources, apply advanced processing on quantitative and qualitative data and build elaborate static or dynamic graphs.

 

 

Program

DAY 1

  • Advanced Data Processing:
    • The numpy library :
      • advanced functions (views, slices)
      • the interface with scipy
    • The pandas library:
      • The import of external data sources,
      • The aggregation of data,
      • The reshaping,
      • Indexing,
      • The merging of data sources
    • The statmodels library:
      • Single and multiple regression,
      • The testing of regression coefficients,
      • The diagnosis of the model,
      • Point and interval prediction
    • The processing of strings, regex
    • Date processing and time series management

DAY 2

    • The generators, itertools, lazy evaluation
    • The database interface (SQL, NoSQL)
    • The Seaborn package:Advanced graphing features (trellis graphs, statistical distributions, heatmap)
    • Interactive graphics with the Bokeh and Plotly packages.

 

Duration
14 hours
Level
Intermediate
Audience
Anyone wishing to discover the advanced Python tools
Participants
8 people maximum
Please contact us for a personnalized offer.

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