GitHub - vikasgupta1812/Udemy-notes: Notes from 'Learning Python for Data Analysis and Visualization' course on Udemy

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Name		Name	Last commit message	Last commit date
Latest commit History 43 Commits
.ipynb_checkpoints		.ipynb_checkpoints
.gitattributes		.gitattributes
.gitignore		.gitignore
Course FAQ.ipynb		Course FAQ.ipynb
Data Project - Election Analysis.ipynb		Data Project - Election Analysis.ipynb
Data Project - Stock Market Analysis.ipynb		Data Project - Stock Market Analysis.ipynb
Intro to Data Project Section.ipynb		Intro to Data Project Section.ipynb
Intro to Data Projects - Titanic.ipynb		Intro to Data Projects - Titanic.ipynb
Lec 07 - Creating Arrays.ipynb		Lec 07 - Creating Arrays.ipynb
Lec 08 - Using arrays and scalars.ipynb		Lec 08 - Using arrays and scalars.ipynb
Lec 09 -Indexing Arrays.ipynb		Lec 09 -Indexing Arrays.ipynb
Lec 10 - Array Transposition.ipynb		Lec 10 - Array Transposition.ipynb
Lec 11 - Universal Array Function.ipynb		Lec 11 - Universal Array Function.ipynb
Lec 12 - Array Processing.ipynb		Lec 12 - Array Processing.ipynb
Lec 13 - Array Input and Output.ipynb		Lec 13 - Array Input and Output.ipynb
Lec 14 - Series.ipynb		Lec 14 - Series.ipynb
Lec 15 - DataFrames.ipynb		Lec 15 - DataFrames.ipynb
Lec 16 - Index Objects.ipynb		Lec 16 - Index Objects.ipynb
Lec 17 -Reindexing.ipynb		Lec 17 -Reindexing.ipynb
Lec 18 -Drop Entry.ipynb		Lec 18 -Drop Entry.ipynb
Lec 19 - Selecting Entries.ipynb		Lec 19 - Selecting Entries.ipynb
Lec 20 - Data Alignment.ipynb		Lec 20 - Data Alignment.ipynb
Lec 21 - Rank and Sort.ipynb		Lec 21 - Rank and Sort.ipynb
Lec 22 - Summary Statistics.ipynb		Lec 22 - Summary Statistics.ipynb
Lec 23 - Missing Data.ipynb		Lec 23 - Missing Data.ipynb
Lec 24 - Index Hierarchy.ipynb		Lec 24 - Index Hierarchy.ipynb
Lec 25 - Reading and Writing Text Files.ipynb		Lec 25 - Reading and Writing Text Files.ipynb
Lec 26 - JSON with Python.ipynb		Lec 26 - JSON with Python.ipynb
Lec 27 - HTML with Python.ipynb		Lec 27 - HTML with Python.ipynb
Lec 28 - Excel with Python.ipynb		Lec 28 - Excel with Python.ipynb
Lec 29 - Merge.ipynb		Lec 29 - Merge.ipynb
Lec 30 -Merge on Index.ipynb		Lec 30 -Merge on Index.ipynb
Lec 31 - Concatenate.ipynb		Lec 31 - Concatenate.ipynb
Lec 32 - Combining DataFrames.ipynb		Lec 32 - Combining DataFrames.ipynb
Lec 33 - Reshaping.ipynb		Lec 33 - Reshaping.ipynb
Lec 34 - Pivoting.ipynb		Lec 34 - Pivoting.ipynb
Lec 35 - Duplicates in DataFrames.ipynb		Lec 35 - Duplicates in DataFrames.ipynb
Lec 36 - Mapping.ipynb		Lec 36 - Mapping.ipynb
Lec 37 - Replace.ipynb		Lec 37 - Replace.ipynb
Lec 38 - Rename Index.ipynb		Lec 38 - Rename Index.ipynb
Lec 39 - Binning.ipynb		Lec 39 - Binning.ipynb
Lec 40 - Outliers.ipynb		Lec 40 - Outliers.ipynb
Lec 41 - Permutation.ipynb		Lec 41 - Permutation.ipynb
Lec 42 - GroupBy on DataFrames.ipynb		Lec 42 - GroupBy on DataFrames.ipynb
Lec 43 - Groupby on Dict and Series.ipynb		Lec 43 - Groupby on Dict and Series.ipynb
Lec 44 - Aggregation.ipynb		Lec 44 - Aggregation.ipynb
Lec 45 - Splitting, Applying and Combining.ipynb		Lec 45 - Splitting, Applying and Combining.ipynb
Lec 46 - Cross-Tabulation.ipynb		Lec 46 - Cross-Tabulation.ipynb
Lec 47 - Installing Seaborn.ipynb		Lec 47 - Installing Seaborn.ipynb
Lec 48 - Histograms.ipynb		Lec 48 - Histograms.ipynb
Lec 49 - Kernel Density Estimation Plots.ipynb		Lec 49 - Kernel Density Estimation Plots.ipynb
Lec 50 - Combining Plot Styles.ipynb		Lec 50 - Combining Plot Styles.ipynb
Lec 51 - Box and Violin Plots.ipynb		Lec 51 - Box and Violin Plots.ipynb
Lec 52 - Regression Plots.ipynb		Lec 52 - Regression Plots.ipynb
Lec 53 - Heatmaps and Clustered Matrices.ipynb		Lec 53 - Heatmaps and Clustered Matrices.ipynb
Lec_28_test.xlsx		Lec_28_test.xlsx
Notes.md		Notes.md
README.md		README.md
lec25.csv		lec25.csv
lec25.txt		lec25.txt
my_array.npy		my_array.npy
my_test_text.txt		my_test_text.txt
mytextdata_out.csv		mytextdata_out.csv
report_summaries_form_3p.csv		report_summaries_form_3p.csv
two_arrays.npz		two_arrays.npz
winequality_red.csv		winequality_red.csv

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Notes from Learning Python for Data Analysis and Visualization Udemy Course: https://www.udemy.com/learning-python-for-data-analysis-and-visualization/ Notebooks can be viewed using nbviewer

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