Desire course net udemy the complete pandas bootcamp 2020 data science with python 202005

Desire course net udemy the complete pandas bootcamp 2020 data science with python 202005

Name	desire-course.-net-udemy-the-complete-pandas-bootcamp-2020-data-science-with-python_202005	DOWNLOAD Copy Link
Total Size	14.3 GB
Total Files	1348
Hash	21F2FECDEB91C5B7A930CA87A51A0324C5C94D37

/
DesireCourse.Net-Udemy - The Complete Pandas Bootcamp 2020 Data Science with Python.torrent	120.4 KB
DesireCourse.Net-Udemy - The Complete Pandas Bootcamp 2020 Data Science with Python_torrent.txt	87.8 KB
[CourseClub.Me].url	0.0 KB
[DesireCourse.Net].url	0.1 KB
[FreeCourseWorld.Com].url	0.1 KB
__ia_thumb.jpg	6.4 KB
desire-course.-net-udemy-the-complete-pandas-bootcamp-2020-data-science-with-python_202005_meta.sqlite	11.3 KB
desire-course.-net-udemy-the-complete-pandas-bootcamp-2020-data-science-with-python_202005_meta.xml	0.9 KB
/19. Time Series Basics/
1. Importing Time Series Data from csv-files.mp4	43.8 MB
1. Importing Time Series Data from csv-files.srt	9.8 KB
10. Advanced Indexing with reindex().mp4	53.0 MB
10. Advanced Indexing with reindex().srt	10.4 KB
2. Converting strings to datetime objects with pd.to_datetime().mp4	60.8 MB
2. Converting strings to datetime objects with pd.to_datetime().srt	11.4 KB
3. Initial Analysis Visualization of Time Series.mp4	36.7 MB
3. Initial Analysis Visualization of Time Series.srt	7.0 KB
4. Indexing and Slicing Time Series.mp4	50.5 MB
4. Indexing and Slicing Time Series.srt	8.7 KB
5. Creating a customized DatetimeIndex with pd.date_range().mp4	120.2 MB
5. Creating a customized DatetimeIndex with pd.date_range().srt	18.4 KB
6. More on pd.date_range().mp4	13.0 MB
6. More on pd.date_range().srt	3.6 KB
7. Downsampling Time Series with resample() (Part 1).mp4	89.7 MB
7. Downsampling Time Series with resample() (Part 1).srt	16.7 KB
8. Downsampling Time Series with resample (Part 2).mp4	51.5 MB
8. Downsampling Time Series with resample (Part 2).srt	10.2 KB
9. The PeriodIndex object.mp4	40.7 MB
9. The PeriodIndex object.srt	7.3 KB
/10. Importing Data/
1. Importing csv-files with pd.read_csv.mp4	95.4 MB
2. Importing messy csv-files with pd.read_csv.mp4	66.3 MB
2. Importing messy csv-files with pd.read_csv.srt	11.1 KB
3. Importing Data from Excel with pd.read_excel().mp4	77.5 MB
3. Importing Data from Excel with pd.read_excel().srt	14.8 KB
4. Importing messy Data from Excel with pd.read_excel().mp4	76.0 MB
4. Importing messy Data from Excel with pd.read_excel().srt	9.0 KB
5. Importing Data from the Web with pd.read_html().mp4	60.8 MB
5. Importing Data from the Web with pd.read_html().srt	9.3 KB
6. Coding Exercise 10.html	0.6 KB
/25. Statistical Concepts/
1. Statistics - Overview, Terms and Vocabulary.mp4	97.9 MB
1. Statistics - Overview, Terms and Vocabulary.srt	15.3 KB
1.1 Overview.pdf	1.0 MB
1.1 Overview_abbyy.gz	47.8 KB
1.1 Overview_djvu.txt	2.4 KB
1.1 Overview_djvu.xml	67.7 KB
1.1 Overview_jp2.zip	7.0 MB
1.1 Overview_scandata.xml	3.6 KB
10. Minimum, Maximum and Range with PythonNumpy.mp4	12.9 MB
10. Minimum, Maximum and Range with PythonNumpy.srt	2.5 KB
11. Percentiles with PythonNumpy.mp4	18.4 MB
11. Percentiles with PythonNumpy.srt	4.2 KB
12. Variance and Standard Deviation with PythonNumpy.mp4	17.1 MB
12. Variance and Standard Deviation with PythonNumpy.srt	4.1 KB
13. Skew and Kurtosis (Theory).mp4	18.9 MB
13. Skew and Kurtosis (Theory).srt	5.4 KB
13.1 skew_kurtosis.pdf	435.3 KB
13.1 skew_kurtosis_abbyy.gz	26.3 KB
13.1 skew_kurtosis_djvu.txt	1.4 KB
13.1 skew_kurtosis_djvu.xml	31.0 KB
13.1 skew_kurtosis_jp2.zip	1.5 MB
13.1 skew_kurtosis_scandata.xml	1.5 KB
14. How to calculate Skew and Kurtosis with scipy.stats.mp4	28.8 MB
14. How to calculate Skew and Kurtosis with scipy.stats.srt	7.0 KB
15. How to generate Random Numbers with Numpy.mp4	26.4 MB
15. How to generate Random Numbers with Numpy.srt	5.7 KB
16. Reproducibility with np.random.seed().mp4	18.1 MB
16. Reproducibility with np.random.seed().srt	4.4 KB
17. Probability Distributions - Overview.mp4	37.4 MB
17. Probability Distributions - Overview.srt	8.1 KB
17.1 Prob_distr.pdf	489.5 KB
17.1 Prob_distr_abbyy.gz	26.5 KB
17.1 Prob_distr_djvu.txt	1.4 KB
17.1 Prob_distr_djvu.xml	51.8 KB
17.1 Prob_distr_jp2.zip	2.4 MB
17.1 Prob_distr_scandata.xml	2.1 KB
18. Discrete Uniform Distributions.mp4	29.6 MB
18. Discrete Uniform Distributions.srt	7.2 KB
19. Continuous Uniform Distributions.mp4	21.1 MB
19. Continuous Uniform Distributions.srt	4.8 KB
2. Downloads for this Section.html	0.1 KB
2.1 Course_Materials_Statistics.zip	13.1 MB
20. The Normal Distribution (Theory).mp4	19.3 MB
20. The Normal Distribution (Theory).srt	7.0 KB
20.1 Normal.pdf	422.3 KB
20.1 Normal_abbyy.gz	18.5 KB
20.1 Normal_djvu.txt	0.9 KB
20.1 Normal_djvu.xml	28.0 KB
20.1 Normal_jp2.zip	1.4 MB
20.1 Normal_scandata.xml	1.5 KB
21. Creating a normally distributed Random Variable.mp4	25.3 MB
21. Creating a normally distributed Random Variable.srt	6.6 KB
22. Normal Distribution - Probability Density Function (pdf) with scipy.stats.mp4	28.3 MB
22. Normal Distribution - Probability Density Function (pdf) with scipy.stats.srt	4.6 KB
23. Normal Distribution - Cumulative Distribution Function (cdf) with scipy.stats.mp4	16.1 MB
23. Normal Distribution - Cumulative Distribution Function (cdf) with scipy.stats.srt	3.3 KB
24. The Standard Normal Distribution and Z-Values.mp4	40.5 MB
24. The Standard Normal Distribution and Z-Values.srt	7.6 KB
25. Properties of the Standard Normal Distribution (Theory).mp4	15.6 MB
25. Properties of the Standard Normal Distribution (Theory).srt	3.8 KB
25.1 standard_normal.pdf	403.4 KB
25.1 standard_normal_abbyy.gz	20.9 KB
25.1 standard_normal_djvu.txt	1.0 KB
25.1 standard_normal_djvu.xml	36.9 KB
25.1 standard_normal_jp2.zip	2.0 MB
25.1 standard_normal_scandata.xml	1.2 KB
26. Probabilities and Z-Values with scipy.stats.mp4	62.2 MB
26. Probabilities and Z-Values with scipy.stats.srt	13.0 KB
27. Confidence Intervals with scipy.stats.mp4	50.4 MB
27. Confidence Intervals with scipy.stats.srt	8.7 KB
28. Covariance and Correlation Coefficient (Theory).mp4	28.9 MB
28. Covariance and Correlation Coefficient (Theory).srt	9.0 KB
28.1 Cov_Corr.pdf	233.6 KB
28.1 Cov_Corr_abbyy.gz	40.3 KB
28.1 Cov_Corr_djvu.txt	2.3 KB
28.1 Cov_Corr_djvu.xml	59.6 KB
28.1 Cov_Corr_jp2.zip	2.0 MB
28.1 Cov_Corr_scandata.xml	1.8 KB
29. Cleaning and preparing the Data - Movies Database (Part 1).mp4	49.3 MB
29. Cleaning and preparing the Data - Movies Database (Part 1).srt	7.8 KB
3. Population vs. Sample.mp4	37.3 MB
3. Population vs. Sample.srt	6.7 KB
30. Cleaning and preparing the Data - Movies Database (Part 2).mp4	32.6 MB
30. Cleaning and preparing the Data - Movies Database (Part 2).srt	7.2 KB
31. How to calculate Covariance and Correlation in Python.mp4	25.2 MB
31. How to calculate Covariance and Correlation in Python.srt	6.4 KB
32. Correlation and Scatterplots – visual Interpretation.mp4	21.0 MB
32. Correlation and Scatterplots – visual Interpretation.srt	6.3 KB
33. What is Linear Regression (Theory).mp4	12.2 MB
33. What is Linear Regression (Theory).srt	3.3 KB
33.1 Regression.pdf	153.8 KB
33.1 Regression_abbyy.gz	15.8 KB
33.1 Regression_djvu.txt	1.0 KB
33.1 Regression_djvu.xml	19.9 KB
33.1 Regression_jp2.zip	1.1 MB
33.1 Regression_scandata.xml	1.2 KB
34. A simple Linear Regression Model with numpy & Scipy.mp4	41.6 MB
34. A simple Linear Regression Model with numpy & Scipy.srt	8.1 KB
35. How to interpret Intercept and Slope Coefficient.mp4	12.9 MB
35. How to interpret Intercept and Slope Coefficient.srt	3.4 KB
35.1 Coeff.pdf	182.0 KB
35.1 Coeff_abbyy.gz	6.9 KB
35.1 Coeff_djvu.txt	0.3 KB
35.1 Coeff_djvu.xml	13.2 KB
35.1 Coeff_jp2.zip	446.8 KB
35.1 Coeff_scandata.xml	0.6 KB
36. Case Study (Part 1) The Market Model (Single Factor Model).mp4	27.6 MB
36. Case Study (Part 1) The Market Model (Single Factor Model).srt	5.9 KB
37. Case Study (Part 2) The Market Model (Single Factor Model).mp4	10.8 MB
37. Case Study (Part 2) The Market Model (Single Factor Model).srt	2.9 KB
4. Visualizing Frequency Distributions with plt.hist().mp4	23.7 MB
4. Visualizing Frequency Distributions with plt.hist().srt	4.6 KB
5. Relative and Cumulative Frequencies with plt.hist().mp4	38.2 MB
5. Relative and Cumulative Frequencies with plt.hist().srt	6.1 KB
6. Measures of Central Tendency (Theory).mp4	21.7 MB
6. Measures of Central Tendency (Theory).srt	6.6 KB
6.1 Central_tendency.pdf	306.5 KB
6.1 Central_tendency_abbyy.gz	30.1 KB
6.1 Central_tendency_djvu.txt	1.7 KB
6.1 Central_tendency_djvu.xml	36.9 KB
6.1 Central_tendency_jp2.zip	2.2 MB
6.1 Central_tendency_scandata.xml	2.1 KB
7. Coding Measures of Central Tendency - Mean and Median.mp4	23.4 MB
7. Coding Measures of Central Tendency - Mean and Median.srt	4.6 KB
8. Coding Measures of Central Tendency - Geometric Mean.mp4	17.4 MB
8. Coding Measures of Central Tendency - Geometric Mean.srt	5.0 KB
9. Variability around the Central Tendency Dispersion (Theory).mp4	29.0 MB
9. Variability around the Central Tendency Dispersion (Theory).srt	8.0 KB
9.1 Dispersion.pdf	306.1 KB
9.1 Dispersion_abbyy.gz	33.1 KB
9.1 Dispersion_djvu.txt	1.8 KB
9.1 Dispersion_djvu.xml	44.3 KB
9.1 Dispersion_jp2.zip	2.3 MB
9.1 Dispersion_scandata.xml	2.1 KB
[CourseClub.Me].url	0.0 KB
[DesireCourse.Net].url	0.1 KB
[FreeCourseWorld.Com].url	0.1 KB
/12. Merging, Joining, and Concatenating Data/
1. Intro.html	0.6 KB
10. Right Joins (without Intersection) with merge().mp4	15.8 MB
10. Right Joins (without Intersection) with merge().srt	2.6 KB
11. Left Joins with merge().mp4	25.3 MB
11. Left Joins with merge().srt	5.3 KB
12. Right Joins with merge().mp4	28.7 MB
12. Right Joins with merge().srt	4.7 KB
13. Joining on different Column Names Indexes.mp4	100.0 MB
13. Joining on different Column Names Indexes.srt	16.7 KB
14. Joining on more than one Column.mp4	40.6 MB
14. Joining on more than one Column.srt	9.7 KB
15. pd.merge() and join().mp4	37.2 MB
15. pd.merge() and join().srt	7.0 KB
16. Coding Exercise 12.html	0.6 KB
2. Adding Rows with append() and pd.concat() (Part 1).mp4	92.3 MB
2. Adding Rows with append() and pd.concat() (Part 1).srt	16.0 KB
3. Adding Rows with pd.concat() (Part 2).mp4	59.7 MB
3. Adding Rows with pd.concat() (Part 2).srt	11.7 KB
4. Arithmetic with Pandas Objects Data Alignment.mp4	40.8 MB
4. Arithmetic with Pandas Objects Data Alignment.srt	9.2 KB
5. EXCURSUS Comparing two DataFrames Identify Differences.html	2.7 KB
6. Outer Joins with merge().mp4	84.0 MB
6. Outer Joins with merge().srt	16.1 KB
7. Inner Joins with merge().mp4	16.3 MB
7. Inner Joins with merge().srt	3.4 KB
8. Outer Joins (without Intersection) with merge().mp4	33.0 MB
8. Outer Joins (without Intersection) with merge().srt	5.6 KB
9. Left Joins (without Intersection) with merge().mp4	22.9 MB
9. Left Joins (without Intersection) with merge().srt	3.9 KB
/23. Python Basics/
1. Intro.mp4	6.2 MB
1. Intro.srt	3.0 KB
10. Operators & Booleans.mp4	62.4 MB
10. Operators & Booleans.srt	11.4 KB
11. Conditional Statements (if, elif, else, while).mp4	90.2 MB
11. Conditional Statements (if, elif, else, while).srt	15.9 KB
12. For Loops.mp4	61.3 MB
12. For Loops.srt	11.5 KB
13. Key words break, pass, continue.mp4	38.5 MB
13. Key words break, pass, continue.srt	7.5 KB
14. Generating Random Numbers.mp4	40.0 MB
14. Generating Random Numbers.srt	8.0 KB
15. User Defined Functions (Part 1).mp4	67.5 MB
15. User Defined Functions (Part 1).srt	10.7 KB
16. User Defined Functions (Part 2).mp4	60.2 MB
16. User Defined Functions (Part 2).srt	7.9 KB
17. User Defined Functions (Part 3).mp4	54.7 MB
17. User Defined Functions (Part 3).srt	8.9 KB
18. Visualization with Matplotlib.mp4	130.3 MB
18. Visualization with Matplotlib.srt	17.2 KB
19. Python Basics.html	0.1 KB
2. First Steps.mp4	35.9 MB
2. First Steps.srt	10.2 KB
20. Python Basics Quiz Solution.mp4	40.1 MB
20. Python Basics Quiz Solution.srt	14.6 KB
3. Variables.mp4	33.0 MB
3. Variables.srt	8.4 KB
4. Data Types Integers and Floats.mp4	51.9 MB
4. Data Types Integers and Floats.srt	8.9 KB
5. Data Types Strings.mp4	81.6 MB
5. Data Types Strings.srt	11.6 KB
6. Data Types Lists (Part 1).mp4	65.7 MB
6. Data Types Lists (Part 1).srt	10.2 KB
7. Data Types Lists (Part 2).mp4	140.9 MB
7. Data Types Lists (Part 2).srt	21.5 KB
8. Data Types Tuples.mp4	43.8 MB
8. Data Types Tuples.srt	7.9 KB
9. Data Types Sets.mp4	22.5 MB
9. Data Types Sets.srt	4.2 KB
/9. ----PART 2 FULL DATA WORKFLOW A-Z----/
1. Welcome to PART 2 Full Data Workflow A-Z.html	0.8 KB
2. Download Part 2 Course Materials.html	0.1 KB
2.1 Course_Materials_Part2.zip	5.6 MB
/24. The Numpy Package/
1. Introduction to Numpy Arrays.mp4	43.1 MB
1. Introduction to Numpy Arrays.srt	9.0 KB
1.1 Numpy_basics.zip	108.3 KB
10. Summary Statistics.mp4	47.0 MB
10. Summary Statistics.srt	8.7 KB
11. Visualization and (Linear) Regression.mp4	88.7 MB
11. Visualization and (Linear) Regression.srt	14.7 KB
12. Numpy.html	0.1 KB
13. Numpy Quiz Solution.mp4	47.7 MB
13. Numpy Quiz Solution.srt	16.8 KB
2. Numpy Arrays Vectorization.mp4	67.9 MB
2. Numpy Arrays Vectorization.srt	10.0 KB
3. Numpy Arrays Indexing and Slicing.mp4	56.0 MB
3. Numpy Arrays Indexing and Slicing.srt	8.4 KB
4. Numpy Arrays Shape and Dimensions.mp4	37.2 MB
4. Numpy Arrays Shape and Dimensions.srt	7.1 KB
5. Numpy Arrays Indexing and Slicing of multi-dimensional Arrays.mp4	77.2 MB
5. Numpy Arrays Indexing and Slicing of multi-dimensional Arrays.srt	11.8 KB
6. Numpy Arrays Boolean Indexing.mp4	46.4 MB
6. Numpy Arrays Boolean Indexing.srt	7.3 KB
7. Generating Random Numbers.mp4	70.8 MB
7. Generating Random Numbers.srt	10.2 KB
8. Performance Issues.mp4	52.3 MB
8. Performance Issues.srt	7.1 KB
9. Case Study Numpy vs. Python Standard Library.mp4	47.8 MB
9. Case Study Numpy vs. Python Standard Library.srt	8.8 KB
/6. Manipulating Elements in a DataFrame Slice +++Important, know the Pitfalls!+++/
1. Intro.html	1.0 KB
2. Best Practice (How you should do it).mp4	55.2 MB
2. Best Practice (How you should do it).srt	11.0 KB
3. Chained Indexing How you should NOT do it (Part 1).mp4	63.0 MB
3. Chained Indexing How you should NOT do it (Part 1).srt	11.0 KB
4. Chained Indexing How you should NOT do it (Part 2).mp4	61.7 MB
4. Chained Indexing How you should NOT do it (Part 2).srt	9.4 KB
5. View vs. Copy.mp4	36.2 MB
5. View vs. Copy.srt	7.1 KB
6. Simple Rules what to do when....mp4	48.1 MB
6. Simple Rules what to do when....srt	9.8 KB
7. Manipulating DataFrames Slices.html	0.1 KB
8. Coding Exercise 6 (Intro).html	0.2 KB
9. Coding Exercise 6 (Solution).mp4	41.3 MB
9. Coding Exercise 6 (Solution).srt	7.4 KB
/16. Advanced Visualization with Seaborn/
1. Intro.html	0.8 KB
2. First Steps in Seaborn.mp4	23.2 MB
2. First Steps in Seaborn.srt	7.2 KB
3. Categorical Plots.mp4	89.3 MB
3. Categorical Plots.srt	17.4 KB
4. Joint Plots Regression Plots.mp4	83.5 MB
4. Joint Plots Regression Plots.srt	14.2 KB
5. Matrixplots Heatmaps.mp4	44.9 MB
5. Matrixplots Heatmaps.srt	10.5 KB
6. Coding Exercise 16.html	0.6 KB
/26. Download .py files/
1. Parts 1 & 2 .py files.html	0.1 KB
1.1 Course_Materials_Part1.zip	1.5 MB
1.2 Course_Materials_Part2.zip	6.5 MB
/13. GroupBy Operations/
1. Intro.mp4	10.6 MB
1. Intro.srt	2.7 KB
10. Replacing NA Values by group-specific Values.mp4	46.9 MB
10. Replacing NA Values by group-specific Values.srt	8.9 KB
11. Generalizing split-apply-combine with apply().mp4	44.9 MB
11. Generalizing split-apply-combine with apply().srt	10.2 KB
12. Hierarchical Indexing with Groupby.mp4	34.5 MB
12. Hierarchical Indexing with Groupby.srt	7.7 KB
13. stack() and unstack().mp4	82.6 MB
13. stack() and unstack().srt	17.0 KB
14. GroupBy 2.html	0.1 KB
15. Coding Exercise 13 (Intro).html	0.2 KB
16. Coding Exercise 13 (Solution).mp4	85.5 MB
16. Coding Exercise 13 (Solution).srt	15.4 KB
2. Understanding the GroupBy Object.mp4	48.5 MB
2. Understanding the GroupBy Object.srt	10.0 KB
3. Splitting with many Keys.mp4	52.3 MB
3. Splitting with many Keys.srt	8.3 KB
4. split-apply-combine explained.mp4	49.4 MB
4. split-apply-combine explained.srt	11.9 KB
5. split-apply-combine applied.mp4	74.1 MB
5. split-apply-combine applied.srt	14.6 KB
6. GroupBy 1.html	0.1 KB
7. Advanced aggregation with agg().mp4	31.7 MB
7. Advanced aggregation with agg().srt	7.0 KB
8. GroupBy Aggregation with Relabeling (NEW - Pandas Version 0.25).mp4	21.6 MB
8. GroupBy Aggregation with Relabeling (NEW - Pandas Version 0.25).srt	5.5 KB
9. Transformation with transform().mp4	37.1 MB
9. Transformation with transform().srt	7.6 KB
/15. Data Preparation and Feature Creation/
1. Intro.html	0.7 KB
10. Scaling Standardization.mp4	59.1 MB
10. Scaling Standardization.srt	9.9 KB
11. Creating Dummy Variables.mp4	57.9 MB
11. Creating Dummy Variables.srt	11.2 KB
12. String Operations.mp4	31.1 MB
12. String Operations.srt	5.5 KB
13. Coding Exercise 15.html	0.6 KB
2. Arithmetic Operations (Part 1).mp4	66.6 MB
2. Arithmetic Operations (Part 1).srt	15.1 KB
3. Arithmetic Operations (Part 2).mp4	61.3 MB
3. Arithmetic Operations (Part 2).srt	14.9 KB
4. TransformationMapping with map().mp4	44.8 MB
4. TransformationMapping with map().srt	8.2 KB
5. Conditional Transformation.mp4	35.0 MB
5. Conditional Transformation.srt	8.8 KB
6. Discretization and Binning with pd.cut() (Part 1).mp4	76.6 MB
6. Discretization and Binning with pd.cut() (Part 1).srt	14.2 KB
7. Discretization and Binning with pd.cut() (Part 2).mp4	34.3 MB
7. Discretization and Binning with pd.cut() (Part 2).srt	6.2 KB
8. Discretization and Binning with pd.qcut().mp4	89.5 MB
8. Discretization and Binning with pd.qcut().srt	16.5 KB
9. Floors and Caps.mp4	41.2 MB
9. Floors and Caps.srt	9.0 KB
/18. ----PART 4 MANAGING TIME SERIES DATA WITH PANDAS----/
1. Welcome to PART 4 Time Series Data with Pandas.html	0.6 KB
2. Download Part 4 Course Materials.html	0.1 KB
2.1 Course_Materials_Part4.zip	851.4 KB
/27. What´s next/
1. Get your special BONUS here!.html	3.6 KB
/7. DataFrame Basics III/
1. Intro.html	0.6 KB
10. Hierarchical Indexing (Part 1).mp4	76.1 MB
10. Hierarchical Indexing (Part 1).srt	13.0 KB
11. Hierarchical Indexing (Part 2).mp4	76.1 MB
11. Hierarchical Indexing (Part 2).srt	15.0 KB
12. String Operations (Part 1).mp4	43.2 MB
12. String Operations (Part 1).srt	9.3 KB
13. String Operations (Part 2).mp4	57.9 MB
13. String Operations (Part 2).srt	12.2 KB
14. Coding Exercise 8 (Intro).html	0.2 KB
15. Coding Exercise 8 (Solution).mp4	61.1 MB
15. Coding Exercise 8 (Solution).srt	10.9 KB
2. Sorting DataFrames with sort_index() and sort_values() (Version 1.0 Update).mp4	72.2 MB
2. Sorting DataFrames with sort_index() and sort_values() (Version 1.0 Update).srt	10.6 KB
3. Ranking DataFrames with rank().mp4	45.6 MB
3. Ranking DataFrames with rank().srt	9.2 KB
4. nunique() and nlargest() nsmallest() with DataFrames.mp4	34.2 MB
4. nunique() and nlargest() nsmallest() with DataFrames.srt	6.5 KB
5. Summary Statistics and Accumulations.mp4	60.3 MB
5. Summary Statistics and Accumulations.srt	12.0 KB
6. The agg() method.mp4	23.9 MB
6. The agg() method.srt	4.3 KB
7. Coding Exercise 7 (Intro).html	0.2 KB
8. Coding Exercise 7 (Solution).mp4	41.7 MB
8. Coding Exercise 7 (Solution).srt	6.1 KB
9. User-defined Functions with apply(), map() and applymap().mp4	77.9 MB
9. User-defined Functions with apply(), map() and applymap().srt	16.9 KB
/8. Visualization with Matplotlib/
1. Intro.html	0.7 KB
2. The plot() method.mp4	73.7 MB
2. The plot() method.srt	11.1 KB
3. Customization of Plots.mp4	108.0 MB
3. Customization of Plots.srt	14.2 KB
4. Histograms (Part 1).mp4	25.8 MB
4. Histograms (Part 1).srt	5.4 KB
5. Histograms (Part 2).mp4	35.8 MB
5. Histograms (Part 2).srt	8.2 KB
6. Barcharts and Piecharts.mp4	21.0 MB
6. Barcharts and Piecharts.srt	4.6 KB
7. Scatterplots.mp4	37.9 MB
7. Scatterplots.srt	8.3 KB
8. Coding Exercise 9 (Intro).html	0.2 KB
9. Coding Exercise 9 (Solution).mp4	38.6 MB
9. Coding Exercise 9 (Solution).srt	5.8 KB
/22. ---APPENDIX PYTHON BASICS, NUMPY & STATISTICS---/
1. Welcome to the Appendix.html	0.4 KB
/2. ---PART 1 PANDAS FROM ZERO TO HERO (BUILDING BLOCKS)---/
1. Intro to Tabular Data Pandas.mp4	19.0 MB
1. Intro to Tabular Data Pandas.srt	5.6 KB
1.1 tabdata.pdf	483.5 KB
1.1 tabdata_abbyy.gz	21.1 KB
1.1 tabdata_djvu.txt	1.2 KB
1.1 tabdata_djvu.xml	28.9 KB
1.1 tabdata_jp2.zip	929.1 KB
1.1 tabdata_scandata.xml	1.5 KB
2. Download Part 1 Course Materials.mp4	19.6 MB
2. Download Part 1 Course Materials.srt	3.0 KB
2.1 Course_Materials_Part1.zip	1.1 MB
/11. Cleaning Data/
1. First Inspection & Handling of inconsistent Data.mp4	71.6 MB
1. First Inspection & Handling of inconsistent Data.srt	13.4 KB
10. Handling Removing Duplicates.mp4	93.0 MB
10. Handling Removing Duplicates.srt	93.0 MB
11. The ignore_index parameter (NEW in Pandas 1.0).mp4	5.9 MB
11. The ignore_index parameter (NEW in Pandas 1.0).srt	2.2 KB
12. Detection of Outliers.mp4	46.2 MB
12. Detection of Outliers.srt	10.7 KB
13. Handling Removing Outliers.mp4	31.1 MB
13. Handling Removing Outliers.srt	7.0 KB
14. Categorical Data.mp4	47.7 MB
14. Categorical Data.srt	9.3 KB
15. Pandas Version 1.0 New dtypes and pd.NA.mp4	19.4 MB
15. Pandas Version 1.0 New dtypes and pd.NA.srt	19.2 MB
16. Coding Exercise 11 (Intro).html	0.2 KB
17. Coding Exercise 11 (Solution).mp4	136.0 MB
17. Coding Exercise 11 (Solution).srt	20.0 KB
2. String Operations.mp4	84.8 MB
2. String Operations.srt	15.2 KB
3. Changing Datatype of Columns with astype().mp4	40.7 MB
3. Changing Datatype of Columns with astype().srt	8.3 KB
4. Intro NA values missing values.mp4	47.9 MB
4. Intro NA values missing values.srt	10.8 KB
5. Detection of missing Values.mp4	93.7 MB
5. Detection of missing Values.srt	17.6 KB
6. Removing missing values.mp4	89.6 MB
6. Removing missing values.srt	18.9 KB
7. Replacing missing values.mp4	25.8 MB
7. Replacing missing values.srt	5.3 KB
8. Intro Duplicates.mp4	21.2 MB
8. Intro Duplicates.srt	6.5 KB
9. Detection of Duplicates.mp4	83.1 MB
9. Detection of Duplicates.srt	15.3 KB
/4. Pandas Series and Index Objects/
1. Intro.html	0.8 KB
10. idxmin() and idxmax().mp4	30.1 MB
10. idxmin() and idxmax().srt	6.2 KB
11. Manipulating Pandas Series.mp4	39.7 MB
11. Manipulating Pandas Series.srt	9.6 KB
12. Pandas Series.html	0.1 KB
13. Coding Exercise 3 (Intro).html	0.2 KB
14. Coding Exercise 3 (Solution).mp4	40.5 MB
14. Coding Exercise 3 (Solution).srt	7.6 KB
15. First Steps with Pandas Index Objects.mp4	45.2 MB
15. First Steps with Pandas Index Objects.srt	6.7 KB
16. Creating Index Objects from Scratch.mp4	15.8 MB
16. Creating Index Objects from Scratch.srt	3.5 KB
17. Changing Row Index with set_index() and reset_index().mp4	78.7 MB
17. Changing Row Index with set_index() and reset_index().srt	12.1 KB
18. Changing Column Labels.mp4	22.2 MB
18. Changing Column Labels.srt	4.0 KB
19. Renaming Index & Column Labels with rename().mp4	29.4 MB
19. Renaming Index & Column Labels with rename().srt	4.9 KB
2. First Steps with Pandas Series.mp4	19.9 MB
2. First Steps with Pandas Series.srt	4.9 KB
20. Pandas Index objects.html	0.1 KB
21. Coding Exercise 4 (Intro).html	0.2 KB
22. Coding Exercise 4 (Solution).mp4	27.6 MB
22. Coding Exercise 4 (Solution).srt	4.7 KB
3. Analyzing Numerical Series with unique(), nunique() and value_counts().mp4	70.4 MB
3. Analyzing Numerical Series with unique(), nunique() and value_counts().srt	17.2 KB
4. Analyzing non-numerical Series with unique(), nunique(), value_counts().mp4	45.0 MB
4. Analyzing non-numerical Series with unique(), nunique(), value_counts().srt	8.8 KB
5. Creating Pandas Series (Part 1).mp4	39.9 MB
5. Creating Pandas Series (Part 1).srt	7.4 KB
6. Creating Pandas Series (Part 2).mp4	28.0 MB
6. Creating Pandas Series (Part 2).srt	6.7 KB
7. Indexing and Slicing Pandas Series.mp4	69.4 MB
7. Indexing and Slicing Pandas Series.srt	11.6 KB
8. Sorting of Series and Introduction to the inplace - parameter.mp4	43.4 MB
8. Sorting of Series and Introduction to the inplace - parameter.srt	10.8 KB
9. nlargest() and nsmallest().mp4	17.6 MB
9. nlargest() and nsmallest().srt	4.3 KB
/3. Pandas Basics (DataFrame Basics I)/
1. Create your very first Pandas DataFrame (from csv).mp4	62.3 MB
1. Create your very first Pandas DataFrame (from csv).srt	10.8 KB
10. Selecting one Column with the dot notation.mp4	8.9 MB
10. Selecting one Column with the dot notation.srt	3.0 KB
11. Zero-based Indexing and Negative Indexing.mp4	10.7 MB
11. Zero-based Indexing and Negative Indexing.srt	3.8 KB
11.1 positions.pdf	198.8 KB
11.1 positions_abbyy.gz	16.0 KB
11.1 positions_djvu.txt	1.0 KB
11.1 positions_djvu.xml	21.0 KB
11.1 positions_jp2.zip	357.5 KB
11.1 positions_scandata.xml	0.9 KB
12. Selecting Rows with iloc (position-based indexing).mp4	68.2 MB
12. Selecting Rows with iloc (position-based indexing).srt	11.6 KB
13. Slicing Rows and Columns with iloc (position-based indexing).mp4	25.5 MB
13. Slicing Rows and Columns with iloc (position-based indexing).srt	5.4 KB
14. Position-based Indexing Cheat Sheets.html	0.5 KB
14.1 pandas-iloc.pdf	73.7 KB
14.1 pandas-iloc_abbyy.gz	34.7 KB
14.1 pandas-iloc_djvu.txt	2.0 KB
14.1 pandas-iloc_djvu.xml	45.7 KB
14.1 pandas-iloc_jp2.zip	710.5 KB
14.1 pandas-iloc_scandata.xml	1.8 KB
15. Selecting Rows with loc (label-based indexing).mp4	22.4 MB
15. Selecting Rows with loc (label-based indexing).srt	3.8 KB
16. Slicing Rows and Columns with loc (label-based indexing).mp4	81.3 MB
16. Slicing Rows and Columns with loc (label-based indexing).srt	11.7 KB
17. Label-based Indexing Cheat Sheets.html	0.8 KB
17.1 Pandas-loc.pdf	69.4 KB
17.1 Pandas-loc_abbyy.gz	32.7 KB
17.1 Pandas-loc_djvu.txt	2.0 KB
17.1 Pandas-loc_djvu.xml	38.0 KB
17.1 Pandas-loc_jp2.zip	689.7 KB
17.1 Pandas-loc_scandata.xml	1.8 KB
18. Indexing and Slicing with reindex().mp4	40.8 MB
18. Indexing and Slicing with reindex().srt	6.4 KB
19. Summary, Best Practices and Outlook.mp4	44.0 MB
19. Summary, Best Practices and Outlook.srt	7.8 KB
2. Pandas Display Options and the methods head() & tail().mp4	42.4 MB
2. Pandas Display Options and the methods head() & tail().srt	7.8 KB
20. Indexing and Slicing.html	0.1 KB
21. Coding Exercise 2 (Intro).mp4	8.5 MB
21. Coding Exercise 2 (Intro).srt	1.8 KB
22. Coding Exercise 2 (Solution).mp4	29.4 MB
22. Coding Exercise 2 (Solution).srt	4.8 KB
23. Advanced Indexing and Slicing (optional).mp4	35.8 MB
23. Advanced Indexing and Slicing (optional).srt	6.3 KB
3. First Data Inspection.mp4	58.7 MB
3. First Data Inspection.srt	14.6 KB
4. Built-in Functions, Attributes and Methods with Pandas.mp4	49.2 MB
4. Built-in Functions, Attributes and Methods with Pandas.srt	10.6 KB
4.1 DataFrame Methods and Attributes.html	0.1 KB
4.2 Pandas Series Methods and Attributes.html	0.1 KB
5. Make it easy TAB Completion and Tooltip.mp4	57.1 MB
6. First Steps.html	0.1 KB
7. Explore your own Dataset Coding Exercise 1 (Intro).mp4	27.8 MB
7. Explore your own Dataset Coding Exercise 1 (Intro).srt	4.4 KB
8. Explore your own Dataset Coding Exercise 1 (Solution).mp4	32.7 MB
8. Explore your own Dataset Coding Exercise 1 (Solution).srt	5.1 KB
9. Selecting Columns.mp4	27.9 MB
9. Selecting Columns.srt	6.7 KB
/21. +++ WHAT´S NEW IN PANDAS VERSION 1.0 - A HANDS-ON GUIDE +++/
1. Intro and Overview.mp4	16.3 MB
1. Intro and Overview.srt	2.6 KB
10. The NEW StringDtype.mp4	33.7 MB
10. The NEW StringDtype.srt	6.3 KB
11. The NEW nullable BooleanDtype.mp4	24.3 MB
11. The NEW nullable BooleanDtype.srt	5.5 KB
12. Addition of the ignore_index parameter.mp4	22.8 MB
12. Addition of the ignore_index parameter.srt	4.5 KB
13. Removal of prior Version Deprecations.mp4	45.0 MB
13. Removal of prior Version Deprecations.srt	7.7 KB
2. How to update Pandas to Version 1.0.html	0.3 KB
3. Downloads for this Section.html	0.1 KB
3.1 Course_Materials_Version_1_0.zip	28.0 KB
4. Important Recap Pandas Display Options (Changed in Version 0.25).mp4	38.3 MB
4. Important Recap Pandas Display Options (Changed in Version 0.25).srt	6.7 KB
5. Info() method - new and extended output.mp4	10.3 MB
5. Info() method - new and extended output.srt	2.1 KB
6. NEW Extension dtypes (nullable dtypes) Why do we need them.mp4	29.7 MB
6. NEW Extension dtypes (nullable dtypes) Why do we need them.srt	5.6 KB
7. Creating the NEW extension dtypes with convert_dtypes().mp4	26.9 MB
7. Creating the NEW extension dtypes with convert_dtypes().srt	4.7 KB
8. NEW pd.NA value for missing values.mp4	29.3 MB
8. NEW pd.NA value for missing values.srt	7.3 KB
9. The NEW nullable Int64Dtype.mp4	18.9 MB
9. The NEW nullable Int64Dtype.srt	4.2 KB
/14. Reshaping and Pivoting DataFrames/
1. Intro.html	0.9 KB
2. Transposing Rows and Columns.mp4	71.8 MB
2. Transposing Rows and Columns.srt	13.3 KB
3. Pivoting DataFrames with pivot().mp4	58.6 MB
3. Pivoting DataFrames with pivot().srt	11.7 KB
4. Limits of pivot().mp4	61.1 MB
4. Limits of pivot().srt	12.7 KB
5. pivot_table().mp4	60.9 MB
5. pivot_table().srt	16.2 KB
6. pd.crosstab().mp4	104.3 MB
6. pd.crosstab().srt	21.7 KB
7. melting DataFrames with melt().mp4	51.9 MB
7. melting DataFrames with melt().srt	11.0 KB
8. Coding Exercise 14.html	0.6 KB
[CourseClub.Me].url	0.0 KB
[DesireCourse.Net].url	0.1 KB
[FreeCourseWorld.Com].url	0.1 KB
/17. ---PART 3 COMPREHENSIVE PROJECT CHALLENGE---/
1. Download Part 3 Course Materials.html	0.1 KB
1.1 Course_Materials_Part3.zip	8.9 MB
2. Olympic Medal Tables (Instruction & Hints).mp4	60.5 MB
2. Olympic Medal Tables (Instruction & Hints).srt	9.6 KB
3. Olympic Medal Tables (Solution Part 1).mp4	40.3 MB
3. Olympic Medal Tables (Solution Part 1).srt	6.7 KB
4. Olympic Medal Tables (Solution Part 2).mp4	135.0 MB
4. Olympic Medal Tables (Solution Part 2).srt	23.4 KB
5. Olympic Medal Tables (Solution Part 3).mp4	28.3 MB
5. Olympic Medal Tables (Solution Part 3).srt	7.1 KB
/5. DataFrame Basics II/
1. Intro.html	0.4 KB
10. Creating Columns based on other Columns.mp4	36.2 MB
10. Creating Columns based on other Columns.srt	8.1 KB
11. Adding Columns with insert().mp4	13.7 MB
11. Adding Columns with insert().srt	3.6 KB
12. Creating DataFrames from Scratch with pd.DataFrame().mp4	45.4 MB
12. Creating DataFrames from Scratch with pd.DataFrame().srt	10.0 KB
13. Adding new Rows (hands-on approach).mp4	17.8 MB
13. Adding new Rows (hands-on approach).srt	3.8 KB
14. DataFrame Basics II.html	0.1 KB
15. Coding Exercise 5 (Intro).html	0.2 KB
16. Coding Exercise 5 (Solution).mp4	60.5 MB
16. Coding Exercise 5 (Solution).srt	10.8 KB
2. Filtering DataFrames by one Condition.mp4	55.5 MB
2. Filtering DataFrames by one Condition.srt	13.0 KB
3. Filtering DataFrames by many Conditions (AND).mp4	27.2 MB
3. Filtering DataFrames by many Conditions (AND).srt	5.3 KB
4. Filtering DataFrames by many Conditions (OR).mp4	32.3 MB
4. Filtering DataFrames by many Conditions (OR).srt	6.0 KB
5. Advanced Filtering with between(), isin() and ~.mp4	68.9 MB
5. Advanced Filtering with between(), isin() and ~.srt	9.2 KB
6. any() and all().mp4	18.4 MB
6. any() and all().srt	4.8 KB
7. Removing Columns.mp4	37.8 MB
7. Removing Columns.srt	6.2 KB
8. Removing Rows.mp4	52.0 MB
8. Removing Rows.srt	8.3 KB
9. Adding new Columns to a DataFrame.mp4	18.7 MB
9. Adding new Columns to a DataFrame.srt	3.9 KB
[CourseClub.Me].url	0.0 KB
[DesireCourse.Net].url	0.1 KB
[FreeCourseWorld.Com].url	0.1 KB
/0. Websites you may like/
[CourseClub.Me].url	0.0 KB
[DesireCourse.Net].url	0.1 KB
[FreeCourseWorld.Com].url	0.1 KB
/1. Getting Started/
1. Overview Student FAQ.mp4	50.8 MB
1. Overview Student FAQ.srt	12.3 KB
2. Tips How to get the most out of this course.mp4	45.7 MB
2. Tips How to get the most out of this course.srt	6.7 KB
3. Did you know that....mp4	32.8 MB
3. Did you know that....srt	5.3 KB
4. More FAQ Important Information.html	5.6 KB
5. Installation of Anaconda.mp4	90.5 MB
5. Installation of Anaconda.srt	9.0 KB
5.1 Installing on Windows.html	0.1 KB
5.2 Installing on macOS.html	0.1 KB
5.3 Installing on Linux.html	0.1 KB
6. Opening a Jupyter Notebook.mp4	68.2 MB
6. Opening a Jupyter Notebook.srt	11.1 KB
7. How to use Jupyter Notebooks.mp4	69.5 MB
7. How to use Jupyter Notebooks.srt	17.3 KB
8. How to tackle Pandas Version 1.0.mp4	20.0 MB
8. How to tackle Pandas Version 1.0.srt	3.4 KB
/20. Time Series Advanced Financial Time Series/
1. Intro.html	1.0 KB
10. Financial Time Series - Covariance and Correlation.mp4	27.0 MB
10. Financial Time Series - Covariance and Correlation.srt	5.6 KB
11. Helpful DatetimeIndex Attributes and Methods.mp4	46.5 MB
11. Helpful DatetimeIndex Attributes and Methods.srt	7.3 KB
12. Filling NA Values with bfill, ffill and interpolation.mp4	82.3 MB
12. Filling NA Values with bfill, ffill and interpolation.srt	12.2 KB
13. Coding Exercise 17.html	0.6 KB
2. Getting Ready (Installing required package).mp4	22.8 MB
2. Getting Ready (Installing required package).srt	2.8 KB
3. Importing Stock Price Data from Yahoo Finance (it still works!).mp4	75.4 MB
3. Importing Stock Price Data from Yahoo Finance (it still works!).srt	10.2 KB
4. Initial Inspection and Visualization.mp4	44.4 MB
4. Initial Inspection and Visualization.srt	6.2 KB
5. Normalizing Time Series to a Base Value (100).mp4	46.4 MB
5. Normalizing Time Series to a Base Value (100).srt	7.9 KB
6. The shift() method.mp4	37.5 MB
6. The shift() method.srt	8.7 KB
7. The methods diff() and pct_change().mp4	42.2 MB
7. The methods diff() and pct_change().srt	8.6 KB
8. Measuring Stock Performance with MEAN Returns and STD of Returns.mp4	46.1 MB
8. Measuring Stock Performance with MEAN Returns and STD of Returns.srt	10.8 KB
9. Financial Time Series - Return and Risk.mp4	56.2 MB
9. Financial Time Series - Return and Risk.srt	10.2 KB
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