We use cookies to help you navigate efficiently and perform certain functions. You will find detailed information about all cookies under each consent category below.
The cookies that are categorized as "Necessary" are stored on your browser as they are essential for enabling the basic functionalities of the site. ...
Necessary cookies are required to enable the basic features of this site, such as providing secure log-in or adjusting your consent preferences. These cookies do not store any personally identifiable data.
Functional cookies help perform certain functionalities like sharing the content of the website on social media platforms, collecting feedback, and other third-party features.
Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics such as the number of visitors, bounce rate, traffic source, etc.
Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.
Advertisement cookies are used to provide visitors with customized advertisements based on the pages you visited previously and to analyze the effectiveness of the ad campaigns.
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.
Install the Anaconda distribution
Introduction to Numpy
Create ndarray objects
Data selection
Add, edit, delete items
Use numpy functions
Enter exit
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
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
->
→ R Language Course: RStudio, Reporting
→ Python Training for Data Science | scientific python
→ Python Training – Data Science (Numpy Pandas Matplotlib)
“ 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. “
“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. “
“ 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!“