In this training science of data we start with the grip of working tools: Jupyter Notebook, Spyder, among others. Then we start with Numpy (numerical Python). We insist on calculation functions: maths, stats, fi nancial, etc. The heart of the training is Pandas. This module allows you to sort, filter, select, cut, truncate, categorize, group, aggregate, rotate, stack, cross, and so on. Pandas does what a spreadsheet and SQL table do and more. Pandas allows you to apply Numpy or other functions. In addition, Pandas can automate procedures and work in volume (parallel computing on multiple processors, on graphics card or on a cluster). Pandas is often the machine learning model foundation, because you have to prepare the data before using it. Finally, Pandas makes it easy to visualize data with modules like Matplotlib and Seaborn. There is also a GeoPandas extension for geomatics to enhance map visualization.

Some specializations and pointed topics not covered are available extra. We will revise them quickly.

Course details

tool

Install the Anaconda distribution

Python for scientific computing: Numpy

Introduction to Numpy
Create ndarray objects
Data selection
Add, edit, delete items
Use numpy functions
Enter exit

Manipulating data with Pandas

Series objects
DataFrames objects
Data selection
Aggregation functions
Merge, Join, Remodeling
Use lambda functions
Make a dynamic crossover (Pivot Table)
Manipulate excel data (csv) and json

Visualize data with Matplotlib

2D curve display
Point cloud display
Histogram display
Web API

Request to an API
Get the answer
Treat the answer
Application: API Twitter, analyze and visualize in time
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Autre(s) cours dans cette catégorie

→ R Language Course: RStudio, Reporting

→ Python Training for Data Science | scientific python

→ Python Training – Data Science (Numpy Pandas Matplotlib)

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Benefits:

• A course material for each participant
• Support of the trainer after the training
• We offer you in public session:
  • Tea, coffee
  • Parking (only in some cities)
  • Wireless internet connection

Préalables :

 
• Basic knowledge of python

Objectifs :

• Use the main numerical calculation libraries including Numpy, Pandas and Matplotlib
• Collect data on a Web API

NOS FORMATEURS

Montréal :

Québec :

Gatineau / Ottawa :

Moncton :

Classe virtuelle (en ligne) :

Preferential*

1274 $

per participant

Duration :3 day(s), is 21 hours.
Hours: 9 am-5pm, 2 coffee breaks.

See the lesson plan in PDF

Locations: Montreal, Gatineau / Ottawa, Quebec City.

See customer reviews

Regular price: 1499 $

*The preferential rate applies if you register at least two participants in the same session.

Formation en ligne

Vidéos de formations sur les logiciels en bureautique

Accéder

Mark Plouffe, Gouvernement du Canada/ Government of Canada

“ I want to thank you both for providing my resources some excellent training(Cobol) over the past 3 days. Mamadou, thank you for being so accommodating on such short notice and for sending your facilitator to Gatineau for this customised and personalised training course. We’ll look forward to continuing our partnership for future training needs. “

Maryse Duguay - Analyste fonctionnelle Base de donnée - Montréal

“J’ai grandement apprécié les méthodes d’enseignement du prof. Le fait que nous soyons un petit groupe a grandement facilité les apprentissages. Il s’adapte à son audience et les exercices sont formateurs. Je recommande fortement. “

Martin Côté - Analyste Assurance Qualité - Travailleur autonome – Montréal

“ Ce fut un plaisir de faire affaires avec Doussou Formation. Ce qui fait LA différence est le service personnalisé totalement à l'écoute des participants ainsi que l'adaptation aux besoins de formation. Flexibilité/Adaptabilité/Professionnalisme/Courtoisie. Merci!“