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[DesireCourse Net] Udemy - Complete Data Wrangling & Data Visualisation With Python

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Title: UdemyGroup: NOGRPSource: Udemy
Info Hash
52C1AF21078E1BC1AFC0316017794C667BF247B5
Source
Unverified
Total Size
3.07 GB
Total Files
100
Seeders
0
Leechers
1
Health
Score
1
Type
Bookware

File List

FileSize
1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/1. Welcome to the Course.mp412.43 MB
1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/1. Welcome to the Course.vtt2.85 KB
1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/2. Data & Script For the Course.html123 B
1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/2.1 Data and Code.zip.zip123.32 MB
1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/3. Python Data Science Environment.mp4105.06 MB
1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/3. Python Data Science Environment.vtt10.18 KB
1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/4. For Mac Users.mp450.07 MB
1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/4. For Mac Users.vtt3.79 KB
1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/5. Introduction to IPythonJupyter.mp4102.69 MB
1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/5. Introduction to IPythonJupyter.vtt17.15 KB
1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/6. ipython in Browser.mp440.48 MB
1. INTRODUCTION TO THE COURSE The Key Concepts and Software Tools/6. ipython in Browser.vtt3.45 KB
2. Read in Data From Different Sources With Pandas/1. What are Pandas.mp485.04 MB
2. Read in Data From Different Sources With Pandas/1. What are Pandas.vtt9.8 KB
2. Read in Data From Different Sources With Pandas/2. Read CSV Data.mp453.86 MB
2. Read in Data From Different Sources With Pandas/2. Read CSV Data.vtt5.66 KB
2. Read in Data From Different Sources With Pandas/3. Read Excel Data.mp442.4 MB
2. Read in Data From Different Sources With Pandas/3. Read Excel Data.vtt3.56 KB
2. Read in Data From Different Sources With Pandas/4. Read in HTML Data.mp4129.55 MB
2. Read in Data From Different Sources With Pandas/4. Read in HTML Data.vtt11.11 KB
3. Data Cleaning/1. Remove NA Values.mp455.95 MB
3. Data Cleaning/1. Remove NA Values.vtt6.47 KB
3. Data Cleaning/2. Missing Values in a Real Dataset.mp436.88 MB
3. Data Cleaning/2. Missing Values in a Real Dataset.vtt6.32 KB
3. Data Cleaning/3. Data Imputation.mp456.41 MB
3. Data Cleaning/3. Data Imputation.vtt8.98 KB
3. Data Cleaning/4. Imputing Qualitative Values.mp420.97 MB
3. Data Cleaning/4. Imputing Qualitative Values.vtt3.35 KB
3. Data Cleaning/5. Theory Behind k-NN Algorithm.mp496.2 MB
3. Data Cleaning/5. Theory Behind k-NN Algorithm.vtt6.54 KB
3. Data Cleaning/6. Use k-NN for Data Imputation.mp444.22 MB
3. Data Cleaning/6. Use k-NN for Data Imputation.vtt6.08 KB
4. Basic Data Wrangling/1. Basic Principles.mp426.51 MB
4. Basic Data Wrangling/1. Basic Principles.vtt4.63 KB
4. Basic Data Wrangling/2. Preliminary Data Explorations.mp464.53 MB
4. Basic Data Wrangling/2. Preliminary Data Explorations.vtt7.78 KB
4. Basic Data Wrangling/3. Basic Data Handling With Conditional Statements.mp449.41 MB
4. Basic Data Wrangling/3. Basic Data Handling With Conditional Statements.vtt4.1 KB
4. Basic Data Wrangling/4. Drop ColumnRow.mp447.63 MB
4. Basic Data Wrangling/4. Drop ColumnRow.vtt4.26 KB
4. Basic Data Wrangling/5. Change Column Name.mp425.18 MB
4. Basic Data Wrangling/5. Change Column Name.vtt3.58 KB
4. Basic Data Wrangling/6. Change the Column Type.mp422.67 MB
4. Basic Data Wrangling/6. Change the Column Type.vtt3.92 KB
4. Basic Data Wrangling/7. Explore Date Related Data.mp425.13 MB
4. Basic Data Wrangling/7. Explore Date Related Data.vtt3.61 KB
4. Basic Data Wrangling/8. Simple Date Related Computations.mp425.27 MB
4. Basic Data Wrangling/8. Simple Date Related Computations.vtt3.77 KB
5. More Data Wrangling/1. Data Grouping.mp497.86 MB
5. More Data Wrangling/1. Data Grouping.vtt8.33 KB
5. More Data Wrangling/2. Data Subsetting and Indexing.mp4101.98 MB
5. More Data Wrangling/2. Data Subsetting and Indexing.vtt7.77 KB
5. More Data Wrangling/3. More Data Subsetting.mp469.37 MB
5. More Data Wrangling/3. More Data Subsetting.vtt7.98 KB
5. More Data Wrangling/4. Extract Information From Strings.mp438.29 MB
5. More Data Wrangling/4. Extract Information From Strings.vtt4.19 KB
5. More Data Wrangling/5. (Fuzzy) String Matching.mp418.6 MB
5. More Data Wrangling/5. (Fuzzy) String Matching.vtt2.72 KB
5. More Data Wrangling/6. Ranking & Sorting.mp482.31 MB
5. More Data Wrangling/6. Ranking & Sorting.vtt7.4 KB
5. More Data Wrangling/7. Concatenate.mp470.05 MB
5. More Data Wrangling/7. Concatenate.vtt7.92 KB
5. More Data Wrangling/8. Merging and Joining.mp496.84 MB
5. More Data Wrangling/8. Merging and Joining.vtt10.7 KB
6. Feature Selection and Transformation/1. Correlation Analysis.mp456.42 MB
6. Feature Selection and Transformation/1. Correlation Analysis.vtt8.6 KB
6. Feature Selection and Transformation/2. Using Correlation to Decide Which Features to Retain.mp434.15 MB
6. Feature Selection and Transformation/2. Using Correlation to Decide Which Features to Retain.vtt5.04 KB
6. Feature Selection and Transformation/3. Univariate Feature Selection.mp439.17 MB
6. Feature Selection and Transformation/3. Univariate Feature Selection.vtt4.59 KB
6. Feature Selection and Transformation/4. Recursive Feature Elimination (RFE).mp436.53 MB
6. Feature Selection and Transformation/4. Recursive Feature Elimination (RFE).vtt4.06 KB
6. Feature Selection and Transformation/5. Theory Behind PCA.mp423.87 MB
6. Feature Selection and Transformation/5. Theory Behind PCA.vtt2.94 KB
6. Feature Selection and Transformation/6. Implement PCA.mp426.72 MB
6. Feature Selection and Transformation/6. Implement PCA.vtt4.08 KB
6. Feature Selection and Transformation/7. Data Standardisation.mp432.47 MB
6. Feature Selection and Transformation/7. Data Standardisation.vtt4.13 KB
6. Feature Selection and Transformation/8. Create a New Feature.mp439.97 MB
6. Feature Selection and Transformation/8. Create a New Feature.vtt5.76 KB
7. Theory Behind Data Visualisation/1. What is Data Visualisation.mp468.35 MB
7. Theory Behind Data Visualisation/1. What is Data Visualisation.vtt9.88 KB
7. Theory Behind Data Visualisation/2. Some Theoretical Principles Behind Data Visualisation.mp466.11 MB
7. Theory Behind Data Visualisation/2. Some Theoretical Principles Behind Data Visualisation.vtt7.11 KB
8. Most Common Data Visualizations/1. Histograms-Visualize the Distribution of Continuous Numerical Variables.mp499.1 MB
8. Most Common Data Visualizations/1. Histograms-Visualize the Distribution of Continuous Numerical Variables.vtt11.72 KB
8. Most Common Data Visualizations/2. Boxplots-Visualize the Distribution of Continuous Numerical Variables.mp440.52 MB
8. Most Common Data Visualizations/2. Boxplots-Visualize the Distribution of Continuous Numerical Variables.vtt5.47 KB
8. Most Common Data Visualizations/3. Scatter plot-Relationship Between Two Numerical Variables.mp4106.83 MB
8. Most Common Data Visualizations/3. Scatter plot-Relationship Between Two Numerical Variables.vtt12.07 KB
8. Most Common Data Visualizations/4. Barplot.mp4170.67 MB
8. Most Common Data Visualizations/4. Barplot.vtt22.51 KB
8. Most Common Data Visualizations/5. Pie Chart.mp437.88 MB
8. Most Common Data Visualizations/5. Pie Chart.vtt5.84 KB
8. Most Common Data Visualizations/6. Line Charts.mp4116.79 MB
8. Most Common Data Visualizations/6. Line Charts.vtt12.01 KB
8. Most Common Data Visualizations/7. More Line Charts.mp418.94 MB
8. Most Common Data Visualizations/7. More Line Charts.vtt2.28 KB
8. Most Common Data Visualizations/8. Some More Plot Types.mp475.99 MB
8. Most Common Data Visualizations/8. Some More Plot Types.vtt10.56 KB

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