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Feuille de route complète LM
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Module 6
Data Analysis with Pandas and Visualization
1
Building Pandas Series and DataFrames
Create a Pandas Series and a DataFrame from Python objects.
2
Loading and Inspecting CSV Data with Pandas
Load data from CSV files into a Pandas DataFrame and inspect it with .head() and .info().
3
Selecting Data with .loc and .iloc
Select rows and columns from a DataFrame using .loc and .iloc.
4
Filtering and Sorting DataFrames
Filter data using boolean conditions and sort a DataFrame by its values.
5
Missing Data: Detection, Removal, and Imputation
Handle missing data by detecting, removing, or imputing values.
6
Grouping and Aggregating Data with Pandas
Group data using .groupby() and compute aggregate statistics.
7
Merging DataFrames with `pd.merge()`
Merge two DataFrames using pd.merge().
8
Matplotlib Basics: Creating Essential Plots
Create basic line, bar, histogram, and scatter plots using Matplotlib.
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Scientific Computing with NumPy
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Foundations of Classical Machine Learning