Language: English (US)
Mastering Data Analysis with Pandas: Techniques and Best Practices for Data Mastery
https://www.udemy.com/course/pandas-data-analytics/
Below is the description of the Course 1. Introduction to Pandas 2. Pandas Series 3. DataFrame 4. Handling missing data in DataFrame 5. Conditional Selection and Reindexing of a DataFrame 6. Data Input and Data Output 7. Data Processing 8. Grouping & Aggregation and Pivot Table 9. Concatenating DataFrames and Inserting new rows 10. Merging and Joining DataFrames 11. Logic Explanation for Merging and Joining of two DataFrames. 12. Cartesian Product between two DataFrames explanation. 13. Handling Duplicates in a DataFrame 14. Handling Strings in a DataFrame In the above syllabus you will find the most lucid explanations covering all the topics related to Pandas module. Happy Learning!!!
Pandas_for_Data_Analytics_-_The_Right_Way_2024.part1.rar
Introduction to Pandas Series, Creating Series , Attributes of a Series, Accessing values within a Series, Deleting a value in a Series, Adding two Series.
Introduction to DataFrames, Creating new DataFrames, Attributes of a DataFrame, Selecting Column/Columns from a DataFrame, Creating a new column in a DataFrame, Dropping rows and columns, Inspecting data within a DataFrame, Selecting subset of rows and columns.
Introduction to missing Data, None Datatype, Representing missing values in an Array and a DataFrame, Dropping Rows and Columns with NaN values, Filling missing values, Forward filling and backward filling Row wise and Column wise, Miscellaneous methods.
Conditionally Selecting values, Multiple Conditional Selection, Resetting and Setting New Index.
Reading data from a CSV File, Writing DataFrame to a CSV File, Writing DataFrame to an Excel File, Reading data from an HTML File, Reading data from a SAS File.
Introduction to Data Processing, Reading first and last rows, Renaming Column names in a DataFrame, Deleting a Column, Dropping Rows and Columns simultaneously, Dropping a range of Rows and Columns, Applying Functions to the columns, Sorting or Ordering a DataFrame, Sorting by a single column, Sorting by multiple columns.
Introduction Grouping and aggregation, Grouping by single column, Grouping by multiple Columns, Pivot Tables.
Concatenation, Combining DataFrames along the horizontal axis, Combining DataFrames along the vertical axis, Adding a new row into a DataFrame, Replacing a row at an index, Inserting a new row at an index.
Merging two or more DataFrames, Inner Join, Left Join, Right Join, Outer Join, Merging on columns with different names, Joining DataFrames using Join function.
Count of unique values in a Column, Determining duplicate rows in a DataFrame, Extracting duplicate rows, Dropping duplicate rows, considering certain Columns for dropping duplicates, Dropping all duplicate rows.
Converting Columns to string dtype, String manipulation using different String functions.
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