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Learn Python Libraries For Data Analysis & Data Manipulation - Panter - 22.12.2022 Learn Python Libraries For Data Analysis & Data Manipulation Last updated 6/2020 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 7.92 GB | Duration: 14h 51m Learn Python Pandas, Matplotlib & Seaborn. Read CSV, Excel, SQL, JSON, HTML etc. Datasets. What you'll learn Python Pandas Library and Its Methods Reading Data from Sources like CSV, Excel, Html, Json, Json API, Dictionary, etc, using Python Pandas Handling Missing Data in Datasets Working with TIme Series Datasets Use of Matplotlib Library For Plotting Graphs like Line Graph, Bar Graph, Histogram, Pie Chart etc. Use of Seaborn Library For Plotting Graphs like Line , Bar, Distplot, Catplot, Swarmplot etc. Exploratory Data Analysis on Titanic Dataset Exploratory Data Analysis on GOT Dataset Exploratory Data Analysis on Historial Stock Data ( From JSON API) Exploratory Data Analysis on Restaruant Tips Dataset Requirements Basic Knowledge of Python Knows how to install applications on computer Description Lecture 2:Introduction to Python PandasLecture 3:How to Install Python Pandas on ComputerLecture 4:Data Structures in Python Pandas Section 2:Pandas SeriesLecture 5:How to Create Pandas Series from ScratchLecture 6:How to Create Pandas Series Using Ndarray and Dictionary Section 3:Pandas DataframesLecture 7:Creating Your First DataframeLecture 8:Creating a Datafram Using Python ListsLecture 9:Create an indexed DataFrame using arraysLecture 10:Getting Data of a Row or Multiple Rows in Pandas DataframeLecture 11:Basic Operations on Pandas Dataframes - Using Some Methods and AttributesLecture 12:Setting and Resetting Index of a DataframeLecture 13:How to Locate Values On the basis of Index Name Section 4:Reading CSV Files - With Exploratory Data Analysis on DatasetLecture 14:Reading CSV Files EDA On GOT Dataset Part 1Lecture 15:Reading CSV Files EDA On GOT Dataset Part 2Lecture 16:Read Excel OR Csv File and Write to an Excel Or CSV File Section 5:Handling Missing DataLecture 17:Handdling Missing Data in Dataframes - Fillna MethodLecture 18:Handdling Missing Data in Dataframes - Fillna Method ContinuedLecture 19:Interpolation in Dataframes - Handling Missing DataLecture 20:Replace Methodd in Dataframes - Handling Missing DataLecture 21:Groupby in Python Pandas on Columns with repeating valuesLecture 22:Concatenate Dataframes and visualize them Section 6:Connecting Pandas Dataframe with MySQL Server DatabaseLecture 23:How to Connect Pandas With MySQL Server DatabaseLecture 24:Use of Merge Method in Python Pandas Section 7:Reshaping DataFrames in PandasLecture 25:Pivot and Pivot_Table Methods in Python PandasLecture 26:Stack and Unstack Methods in Python PandasLecture 27:Melt Method for Data Manipulation in PandasLecture 28:Crosstab method in Python Pandas Section 8:Working with Time Series Data in PandasLecture 29:DatetimeIndex in Python Pandas - Time SeriesLecture 30:date_range() method in Python Pandas - Time SeriesLecture 31:to_datetime() Method in Python Pandas Section 9:Working with JSON Data Using JSON Module and Pandas ModuleLecture 32:What is JSONLecture 33:What is an API ?Lecture 34:JSON API Weather Data Analysis Project Using Python Pandas and MatplotlibLecture 35:Stock Price Data From JSON API Analysis using Python Libraries Section 10:EDA on Titanic Dataset from ScratchLecture 36:Exploratory Data Analysis on Titanic Dataset - Pie Chart and DropLecture 37:Correlation Matrix or Heatmap using Seaborn EDA on Titanic DatasetLecture 38:Analysis of Parch and Sibsp Columns in Titanic Dataset - 3 Graphs Side By SideLecture 39:Histogram Plot and Kernel Density Estimation Using Python Section 11:Restaurant Tips DatasetLecture 40:Scatter Plot using Python Libraries on Tips Dataset Overview Section 1: Introduction Lecture 1 Introduction Lecture 2 Introduction to Python Pandas Lecture 3 How to Install Python Pandas on Computer Lecture 4 Data Structures in Python Pandas Section 2: Pandas Series Lecture 5 How to Create Pandas Series from Scratch Lecture 6 How to Create Pandas Series Using Ndarray and Dictionary Section 3: Pandas Dataframes Lecture 7 Creating Your First Dataframe Lecture 8 Creating a Datafram Using Python Lists Lecture 9 Create an indexed DataFrame using arrays Lecture 10 Getting Data of a Row or Multiple Rows in Pandas Dataframe Lecture 11 Basic Operations on Pandas Dataframes - Using Some Methods and Attributes Lecture 12 Setting and Resetting Index of a Dataframe Lecture 13 How to Locate Values On the basis of Index Name Section 4: Reading CSV Files - With Exploratory Data Analysis on GOT Dataset Lecture 14 Reading CSV Files EDA On GOT Dataset Part 1 Lecture 15 Reading CSV Files EDA On GOT Dataset Part 2 Lecture 16 Read Excel OR Csv File and Write to an Excel Or CSV File Lecture 17 EDA on GOT Data Part 3 - Grouped Bar Chart Lecture 18 What is a Box Plot or Box Whisker Plot ? Section 5: Handling Missing Data Lecture 19 Handdling Missing Data in Dataframes - Fillna Method Lecture 20 Handdling Missing Data in Dataframes - Fillna Method Continued Lecture 21 Interpolation in Dataframes - Handling Missing Data Lecture 22 Replace Methodd in Dataframes - Handling Missing Data Lecture 23 Groupby in Python Pandas on Columns with repeating values Lecture 24 Concatenate Dataframes and visualize them Section 6: Connecting Pandas Dataframe with MySQL Server Database Lecture 25 How to Connect Pandas With MySQL Server Database Lecture 26 Use of Merge Method in Python Pandas Section 7: Reshaping DataFrames in Pandas Lecture 27 Pivot and Pivot_Table Methods in Python Pandas Lecture 28 Stack and Unstack Methods in Python Pandas Lecture 29 Melt Method for Data Manipulation in Pandas Lecture 30 Crosstab method in Python Pandas Section 8: Working with Time Series Data in Pandas Lecture 31 DatetimeIndex in Python Pandas - Time Series Lecture 32 date_range() method in Python Pandas - Time Series Lecture 33 to_datetime() Method in Python Pandas Section 9: Working with JSON Data Using JSON Module and Pandas Module Lecture 34 What is JSON Lecture 35 What is an API ? Lecture 36 JSON API Weather Data Analysis Project Using Python Pandas and Matplotlib Lecture 37 Stock Price Data From JSON API Analysis using Python Libraries Section 10: EDA on Titanic Dataset from Scratch Lecture 38 Exploratory Data Analysis on Titanic Dataset - Pie Chart and Drop Lecture 39 Correlation Matrix or Heatmap using Seaborn EDA on Titanic Dataset Lecture 40 Analysis of Parch and Sibsp Columns in Titanic Dataset - 3 Graphs Side By Side Lecture 41 Histogram Plot and Kernel Density Estimation Using Python Section 11: Restaurant Tips Dataset Lecture 42 Scatter Plot using Python Libraries on Tips Dataset Lecture 43 FacetGrid Plot in Seaborn Library on Tips Dataset Lecture 44 3D Plot Using MatplotLib in Python - Introduction Section 12: Graphical Analysis on Misc Datasets Lecture 45 Stacked Bar Chart Plot Using Python Matplotlib on Cricket Series Data Lecture 46 Code For Grouped Bar Chart Using Matplotlib Lecture 47 Lmplot - Regression and Scatter - On Flights Dataset Section 13: Read_html() Method in Pandas Lecture 48 Read_html in Python Pandas Reading Table from a website Lecture 49 Creating HTML Table and Reading Data from Local Html File Section 14: Iris Dataset Lecture 50 Seaborn Pairplot Example on Iris Dataset Beginner Python Developers curious about Data Science,College or School Students who want to Learn Data Analysis Download from RapidGator Download from DDownload Archive Password: "English name of the Old Continent" [First Letter Capital] |