Full Day Exploratory Data Analysis, Charting Pandas MATPLOT(PAID 6 hrs) $99

mar. 2 octobre à 15:00

Fuseau horaire : Paris (GMT+02:00)

Mathmatter Tutoring
Jackson Heights
États-Unis
Queens

Data Wrangling, Exploratory Data Analysis, and Feature Engineering in Pandas Python Class PPT

https://docs.google.com/presentation/d/1PHuf4U2xEO_ikI_F1zZHIqeNnBSo5Eqxw-fAY6BV9-k/edit?usp=sharing

NoteBook: https://notebooks.azure.com/shivgan3/libraries/DataWranglingEDA RESEARCH DESIGN AND PYTHON PANDAS / DATA WRANGLING TERMS AND CONCEPTS Walkthrough the data science workflow using a case study in the Pandas library Import, format and clean data using the Pandas Library Draw Parallels with Excel / SQL STATISTICAL FUNDAMENTALS I Understand the utility of difference data structures Use NumPy and Pandas libraries to analyze datasets using basic summary statistics: mean, median, mode, max, min, quartile, inter-quartile, range, variance, standard deviation and correlation Create data visualization - scatter plots, scatter matrix, line graph, box blots, and histograms- to discern characteristics and trends in a dataset Identify a normal distribution within a dataset using summary statistics and visualization Difference between Normalization and Standardization STATISTICAL FUNDAMENTALS II Explain the difference between causation vs. correlation (rank correlation and pearson) MORE INPUTS ON EXPLORATORY USING PANDAS Deeper insight into exploratory data analysis Correlation Matrix MISSING DATA Handling Missing data

Source: https://www.meetup.com/fr-FR/New-York-Python-SQL-Bootcamp-Data-Science-Analytics/events/254554516/


Mathmatter Tutoring
Jackson Heights
États-Unis

Technologie
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