Udemy Advanced Data Analysis and Wrangling with Python Pandas

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Download Free Download : Udemy Advanced Data Analysis and Wrangling with Python Pandas
mp4 | Video: h264,1280X720 | Audio: AAC, 44.1 KHz
Genre:eLearning | Language: English | Size:14.63 GB
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Files Included :

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1 Introduction.mp4 (58.32 MB)
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2 What makes this course different.mp4 (82.37 MB)
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3 What is pandas.mp4 (246.14 MB)
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4 Course content and structure.mp4 (151.71 MB)
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1 Basics of transformation.mp4 (262.1 MB)
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1 1 transformation.zip (10.98 MB)
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2 Time series transform lag, shift, diff and pct change.mp4 (124.24 MB)
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3 The transform( ) function itself.mp4 (153.27 MB)
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4 User Defined Functions (UDF) for transformation.mp4 (204.53 MB)
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1 Apply.mp4 (136.97 MB)
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1 1 realtor-data.zip (10.21 MB)
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2 Map.mp4 (64.82 MB)
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3 Lambda Functions.mp4 (80.93 MB)
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1 Study tips.mp4 (112.21 MB)
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1 Introduction to the Split-Apply-Combine Strategy in data analytics.mp4 (115.45 MB)
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1 1 data.zip (21.81 MB)
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2 Groupby basics.mp4 (108.34 MB)
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2 1 data.zip (21.81 MB)
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3 Aggregationstatistics by group.mp4 (175.02 MB)
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4 The agg function and California restaurants.mp4 (84.36 MB)
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5 Transformation by group & stock prices.mp4 (184.78 MB)
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6 Caveat on transformation by group.mp4 (109.05 MB)
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1 String data types in pandas, concatenate & change cases.mp4 (232.89 MB)
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1 1 templates.zip (6.56 KB)
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2 Split strings.mp4 (54.3 MB)
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3 Replace, strip, pad, zerofill strings.mp4 (143.2 MB)
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4 Removing prefixsuffix, string slicing, length & count.mp4 (102.13 MB)
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1 How pandas store date and time.mp4 (29.53 MB)
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1 1 data.zip (349.89 KB)
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2 The time stamp.mp4 (131.11 MB)
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3 Frequencies Part 1.mp4 (140.46 MB)
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4 Frequences Part 2.mp4 (140.87 MB)
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5 The dt accessor magic.mp4 (107.45 MB)
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6 Date & time calculations Absolute Time Delta.mp4 (64.07 MB)
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7 More sensible date & time calculations Offsets.mp4 (152.03 MB)
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8 DateTime resampling the basics.mp4 (159.37 MB)
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9 DateTime resampling by group.mp4 (136.67 MB)
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1 Reshape from long to wide formats pivot( ).mp4 (249.91 MB)
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1 1 data.zip (2.26 MB)
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2 Reshapepivot from long to wide with multiple columns.mp4 (53.06 MB)
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3 Excel-style pivot tables.mp4 (200.64 MB)
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4 Differences between pivot( ) and pivot table( ).mp4 (22.02 MB)
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5 Reshape from wide to long format melt( ).mp4 (183.56 MB)
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6 Financial ratios case study.mp4 (286.91 MB)
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1 Introduction to joining data frames.mp4 (91.13 MB)
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1 1 data.zip (2.41 MB)
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2 Vertical merge (concat).mp4 (104.14 MB)
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2 1 data.zip (2.42 MB)
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3 Horizontal merge inner join.mp4 (112.18 MB)
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4 Horizontal merge outerleftright joins.mp4 (134.73 MB)
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5 Financial ratios case setup.mp4 (73.88 MB)
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6 Financial ratios case merge.mp4 (110.29 MB)
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7 Financial ratios case ratios calculation.mp4 (116.7 MB)
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8 Financial ratios case solutions.mp4 (124 MB)
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1 The basic idea of rolling windows.mp4 (79.81 MB)
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1 1 data.zip (4.93 MB)
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2 Moving windows basics.mp4 (144.09 MB)
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2 1 data.zip (4.93 MB)
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3 Moving windows by group.mp4 (61.86 MB)
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4 Exponential moving averages.mp4 (25.59 MB)
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1 Introduction to visualization.mp4 (23.28 MB)
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1 1 data.zip (5.65 MB)
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2 Preparation and setup.mp4 (81.43 MB)
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3 Line plots.mp4 (194.45 MB)
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4 Subplots.mp4 (72.58 MB)
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5 Bar plots.mp4 (27.1 MB)
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6 Scatter plots.mp4 (61.15 MB)
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7 Histograms.mp4 (15.75 MB)
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8 Area plots.mp4 (12.42 MB)
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9 Pie charts.mp4 (6.85 MB)
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1 Install Python and Pandas.mp4 (68.84 MB)
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2 Install Jupyter NotebookLab.mp4 (59.4 MB)
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1 Introduction to the case.mp4 (118.06 MB)
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1 1 data.zip (5.09 MB)
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2 Data cleaning and preparation.mp4 (149.1 MB)
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2 1 data.zip (5.09 MB)
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3 Calculating stock momentum.mp4 (158.83 MB)
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4 Calculating forward returns.mp4 (78.35 MB)
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5 Forming decile porfolios.mp4 (64.19 MB)
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6 Calculating the results.mp4 (61.29 MB)
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7 Visualizing the results.mp4 (100.84 MB)
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1 Introduction to NumPy.mp4 (167.2 MB)
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2 How to create numpy arrays.mp4 (103.75 MB)
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3 How to create special arrays.mp4 (131 MB)
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4 How to reshape numpy arrays.mp4 (74.51 MB)
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5 How to generate random numbers in NumPy.mp4 (234.37 MB)
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6 How to do random shuffling and selections in NumPy.mp4 (81.65 MB)
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7 Element-wise computations & broadcasting.mp4 (130.8 MB)
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8 Matrix math in NumPy.mp4 (197.79 MB)
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9 NumPy's indexing approach.mp4 (263.53 MB)
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1 Pandas vs NumPy.mp4 (39.86 MB)
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2 Basics of series.mp4 (233.75 MB)
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3 Advanced series operations.mp4 (126.02 MB)
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1 Data Frames Basics.mp4 (178.33 MB)
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2 Data Frame basics operations and Gotchas!.mp4 (92.11 MB)
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3 Data Frame computations and new columns.mp4 (99.43 MB)
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4 Useful data frame methods.mp4 (153.94 MB)
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5 Add and drop columns.mp4 (62.95 MB)
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1 Overview of Data File Formats.mp4 (91.84 MB)
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1 1 data files.zip (11.41 MB)
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2 How to Read CSV files.mp4 (145.97 MB)
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2 1 data files.zip (11.41 MB)
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3 Read CSV Files with DateTime Columns.mp4 (162.98 MB)
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4 Dataset with headers and footers (Fama-French).mp4 (56.14 MB)
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5 How to write to CSV files.mp4 (56.13 MB)
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6 How to read and write Parquet files.mp4 (120.19 MB)
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7 How to read and write tab-deliminated and other formats.mp4 (22.58 MB)
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8 How to read and write JSON from the web.mp4 (424.84 MB)
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1 Basic data selection in data frames.mp4 (262.94 MB)
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1 1 california restaurants.zip (150.94 KB)
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2 Gotchas!.mp4 (126.28 MB)
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3 The loc selector.mp4 (259.34 MB)
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4 How to conditionally modify rows using loc selector.mp4 (161.26 MB)
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5 The iloc selector.mp4 (116.09 MB)
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6 Reset the index.mp4 (29.19 MB)
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7 Filter rows with logical conditions.mp4 (277.78 MB)
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8 Chaining complex operations in pandas.mp4 (112.01 MB)
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1 Sort by a single column.mp4 (71.72 MB)
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1 1 california restaurants.zip (150.94 KB)
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2 Sort by multiple columns.mp4 (181.05 MB)
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3 Counting rows & values.mp4 (60.5 MB)
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4 Finding unique values.mp4 (105.19 MB)
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5 Duplicated values part 1.mp4 (130.92 MB)
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6 Duplicated values part 2.mp4 (127.64 MB)
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1 How to find missing values.mp4 (192.35 MB)
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1 1 data.zip (210 KB)
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2 Missing value propogation.mp4 (302.07 MB)
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3 How to fill missing values basics.mp4 (16.9 MB)
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4 How to forward and backward fill missing values in a time-series.mp4 (109.53 MB)
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5 How to fill missing values with averages.mp4 (186.1 MB)
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6 How to use the replace method to good effect.mp4 (57.57 MB)
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7 How to interpolate missing values in a time-series.mp4 (59.23 MB)
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1 Aggregation vs transformation.mp4 (153.71 MB)
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1 1 aggregation data.zip (10.97 MB)
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2 Aggregation basics.mp4 (224.15 MB)
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2 1 aggregation data.zip (10.97 MB)
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3 Multiple statistics for multiple columns at once.mp4 (37.09 MB)
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4 Specific statistics for specific columns at once.mp4 (119.29 MB)
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5 idxmax and idxmin.mp4 (64.87 MB)
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6 Pandas build-in aggregation functions.mp4 (84.56 MB)
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7 Pandas statistic functions.mp4 (59.43 MB)
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8 User Defined Functions (UDF) for aggregation.mp4 (115.44 MB)
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8.35 GB | 00:30:36 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English​

Files Included :

Spoiler

1 Introduction to Bussiness and Data (110.35 MB)
1 1 Supported Files-PPTs (23.96 MB)
1 Data Gathering and API (249.81 MB)
2 Linear Algebra and Advance mathematics in Data Analytics (118.41 MB)
1 Capstone Project (56.72 MB)
2 Project Solution Part-1 (332.35 MB)
3 Project Solution Part-2 (253.59 MB)
4 Project Solution Part-3 (151.28 MB)
1 Python Basics and Jupyter Notebook (108.9 MB)
2 Python Basics and Jupyter Notebook- Lab Session (158.4 MB)
3 Python Basics and Jupyter Notebook- Lab Session Continued (139.82 MB)
1 Basic Python Syntax (172.04 MB)
2 Basic Python Syntax Practical (154.64 MB)
3 Basic Python Syntax Practical Continued (103.02 MB)
4 Basic Python Syntax Practical Continued (193.72 MB)
5 Basic Python Syntax Practical Continued (147.24 MB)
6 Conditional Programming in Python (82.24 MB)
7 Conditional Programming in Python Practical (212.46 MB)
8 Conditional Programming in Python Practical Continued (152.35 MB)
9 Conditional Programming in Python Practical Continued (225.12 MB)
1 Functions and Sequences (124.48 MB)
2 Functions and Sequences Practicle session (112.21 MB)
3 Functions and Sequences Practicle session Continued (162.56 MB)
4 Functions and Sequences Practicle session Continued (166.58 MB)
5 Functions and Sequences Practicle session Continued (169.33 MB)
6 Functions and Sequences Practicle session Continued (163.58 MB)
1 Object Oriented Programming (OOPS) and Numpy (115.9 MB)
2 Object Oriented Programming (OOPS) and Numpy Practical session (185.15 MB)
3 Object Oriented Programming (OOPS) and Numpy Practical session Continued (133.06 MB)
4 Object Oriented Programming (OOPS) and Numpy Practical session continued (187.8 MB)
5 Object Oriented Programming (OOPS) and Numpy Practical session continued (205.49 MB)
6 Object Oriented Programming (OOPS) and Numpy Practical session continued (92.5 MB)
1 Pandas Library and Data Manipulation (182.1 MB)
2 Pandas Library and Data Manipulation Part-2 (194.5 MB)
3 Pandas Library and Data Manipulation Part-3 (203.06 MB)
1 Working with Files and Data Importing (233.91 MB)
2 Working with Files and Data Importing (Part-2) (337.52 MB)
3 Working with Files and Data Importing (Part-3) (137.54 MB)
1 Data Cleaning and Preprocessing (274.51 MB)
2 Data Cleaning and Preprocessing Part- 3 (278.92 MB)
3 Pandas Methods and Operations (129.37 MB)
4 Pandas Methods and Operations Part-2 (284.41 MB)
5 Pandas Methods and Operations Part-3 (169.34 MB)
6 Assignment (177.99 MB)
7 Data Cleaning and Preprocessing Part-2 (248.03 MB)
8 Assignment Solution (244.56 MB)
1 Exploratory Data Analysis (EDA) (227.2 MB)
2 Exploratory Data Analysis (EDA) Part-2 (262.27 MB)

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