[FreeCourseSite.com] Udemy - Data Analysis with Pandas and Python

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[FreeCourseSite.com] Udemy - Data Analysis with Pandas and Python

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收录时间：2021-03-22
最近下载：2024-12-10

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文件列表

  • 1. Installation and Setup/7. MacOS - Create conda Environment and Install pandas and Jupyter Notebook.mp4 117.9 MB
  • 1. Installation and Setup/11. Windows - Create conda Environment and Install pandas and Jupyter Notebook.mp4 117.2 MB
  • 1. Installation and Setup/8. MacOS - Unpack Course Materials + The Start and Shutdown Process.mp4 116.2 MB
  • 5. DataFrames II Filtering Data/1. This Module's Dataset + Memory Optimization.mp4 102.6 MB
  • 1. Installation and Setup/5. MacOS - Install Anaconda Distribution.mp4 95.4 MB
  • 2. BONUS Python Crash Course/8. String Methods.mp4 78.3 MB
  • 11. Working with Dates and Times in Datasets/15. Timeseries Offsets.mp4 78.2 MB
  • 11. Working with Dates and Times in Datasets/12. Selecting Rows from a DataFrame with a DateTimeIndex.mp4 77.9 MB
  • 1. Installation and Setup/6. MacOS - Access the Terminal Application.mp4 76.6 MB
  • 4. DataFrames I Introduction/2. Shared Methods and Attributes between Series and DataFrames.mp4 70.8 MB
  • 6. DataFrames III Data Extraction/3. Retrieve Rows by Index Label with loc Accessor.mp4 64.1 MB
  • 3. Series/8. Create Series from Dataset with the pd.read_csv Method.mp4 63.3 MB
  • 6. DataFrames III Data Extraction/8. Rename Index Labels or Columns in a DataFrame.mp4 60.9 MB
  • 2. BONUS Python Crash Course/7. Custom Functions.mp4 59.2 MB
  • 2. BONUS Python Crash Course/10. Index Positions and Slicing.mp4 58.3 MB
  • 11. Working with Dates and Times in Datasets/13. Timestamp Object Attributes and Methods.mp4 56.8 MB
  • 2. BONUS Python Crash Course/11. Dictionaries.mp4 56.4 MB
  • 2. BONUS Python Crash Course/4. Operators.mp4 53.1 MB
  • 4. DataFrames I Introduction/1. Intro to DataFrames I Module.mp4 52.2 MB
  • 12. Input and Output in pandas/6. Import Excel File into pandas with the read_excel Method.mp4 51.6 MB
  • 1. Installation and Setup/12. Windows - Unpack Course Materials + The Startdown and Shutdown Process.mp4 49.7 MB
  • 8. MultiIndex/6. Extract Rows from a MultiIndex DataFrame.mp4 49.3 MB
  • 12. Input and Output in pandas/7. Export Excel File with the to_excel Method.mp4 49.3 MB
  • 3. Series/19. Extract Series Values by Index Label.mp4 48.5 MB
  • 6. DataFrames III Data Extraction/5. Passing second arguments to the loc and iloc Accessors.mp4 48.1 MB
  • 8. MultiIndex/2. Create a MultiIndex on a DataFrame with the set_index Method.mp4 47.9 MB
  • 2. BONUS Python Crash Course/9. Lists.mp4 46.7 MB
  • 11. Working with Dates and Times in Datasets/14. The pd.DateOffset Object.mp4 46.0 MB
  • 12. Input and Output in pandas/3. Quick Object Conversions.mp4 45.8 MB
  • 11. Working with Dates and Times in Datasets/11. Import Financial Data Set with pandas_datareader Library.mp4 43.7 MB
  • 3. Series/21. Use the get Method to Retrieve a Value for an index label in a Series.mp4 43.1 MB
  • 12. Input and Output in pandas/5. Install xlrd and openpyxl Libraries to Read and Write Excel Files.mp4 42.1 MB
  • 6. DataFrames III Data Extraction/4. Retrieve Rows by Index Position with iloc Accessor.mp4 41.5 MB
  • 6. DataFrames III Data Extraction/2. Use the set_index and reset_index methods to define a new DataFrame index.mp4 41.1 MB
  • 1. Installation and Setup/10. Windows - Install Anaconda Distribution.mp4 40.5 MB
  • 6. DataFrames III Data Extraction/7. Set Multiple Values in a DataFrame.mp4 40.4 MB
  • 8. MultiIndex/7. The transpose Method on a MultiIndex DataFrame.mp4 37.4 MB
  • 8. MultiIndex/5. The sort_index Method on a MultiIndex DataFrame.mp4 36.9 MB
  • 1. Installation and Setup/1. Introduction to Data Analysis with Pandas and Python.mp4 35.7 MB
  • 13. Visualization/2. Use the plot Method to Render a Line Chart.mp4 34.9 MB
  • 1. Installation and Setup/13. Intro to the Jupyter Notebook Interface.mp4 34.9 MB
  • 11. Working with Dates and Times in Datasets/10. Install pandas-datareader Library.mp4 34.6 MB
  • 2. BONUS Python Crash Course/6. Built-in Functions.mp4 34.6 MB
  • 2. BONUS Python Crash Course/3. Basic Data Types.mp4 34.0 MB
  • 7. Working with Text Data/1. Intro to the Working with Text Data Section.mp4 33.9 MB
  • 11. Working with Dates and Times in Datasets/16. The Timedelta Object.mp4 33.8 MB
  • 10. Merging, Joining, and Concatenating DataFrames/3. The pd.concat Method, Part 2.mp4 32.1 MB
  • 5. DataFrames II Filtering Data/2. Filter a DataFrame Based on A Condition.mp4 28.7 MB
  • 13. Visualization/4. Creating Bar Graphs to Show Counts.mp4 28.6 MB
  • 12. Input and Output in pandas/4. Export CSV File with the to_csv Method.mp4 28.6 MB
  • 10. Merging, Joining, and Concatenating DataFrames/6. Outer Joins.mp4 27.2 MB
  • 1. Installation and Setup/17. Import Libraries into Jupyter Notebook.mp4 27.1 MB
  • 2. BONUS Python Crash Course/5. Variables.mp4 25.2 MB
  • 13. Visualization/3. Modifying Plot Aesthetics with matplotlib Templates.mp4 25.1 MB
  • 4. DataFrames I Introduction/14. Convert DataFrame Column Types with the astype Method.mp4 25.0 MB
  • 6. DataFrames III Data Extraction/1. Intro to the DataFrames III Module + Import Dataset.mp4 24.5 MB
  • 9. The GroupBy Object/2. First Operations with groupby Object.mp4 24.2 MB
  • 11. Working with Dates and Times in Datasets/5. The pd.to_datetime() Method.mp4 24.0 MB
  • 10. Merging, Joining, and Concatenating DataFrames/9. Merging by Indexes with the left_index and right_index Parameters.mp4 23.8 MB
  • 8. MultiIndex/14. Use the pivot_table method to create an aggregate summary of a DataFrame.mp4 23.2 MB
  • 10. Merging, Joining, and Concatenating DataFrames/2. The pd.concat Method, Part 1.mp4 22.8 MB
  • 13. Visualization/5. Creating Pie Charts to Represent Proportions.mp4 22.5 MB
  • 9. The GroupBy Object/7. Iterating through Groups.mp4 22.4 MB
  • 1. Installation and Setup/2. About Me.mp4 22.3 MB
  • 10. Merging, Joining, and Concatenating DataFrames/1. Intro to the Merging, Joining, and Concatenating Section.mp4 22.0 MB
  • 10. Merging, Joining, and Concatenating DataFrames/7. Left Joins.mp4 22.0 MB
  • 8. MultiIndex/3. Extract Index Level Values with the get_level_values Method.mp4 21.7 MB
  • 9. The GroupBy Object/4. Methods on the Groupby Object and DataFrame Columns.mp4 21.5 MB
  • 10. Merging, Joining, and Concatenating DataFrames/8. The left_on and right_on Parameters.mp4 21.2 MB
  • 1. Installation and Setup/14. Cell Types and Cell Modes in Jupyter Notebook.mp4 20.9 MB
  • 8. MultiIndex/1. Intro to the MultiIndex Module.mp4 20.9 MB
  • 6. DataFrames III Data Extraction/6. Set New Value for a Specific Cell or Cells In a Row.mp4 20.9 MB
  • 6. DataFrames III Data Extraction/13. Filter A DataFrame with the query method.mp4 20.9 MB
  • 14. Options and Settings in pandas/2. Changing pandas Options with Attributes and Dot Syntax.mp4 20.8 MB
  • 12. Input and Output in pandas/2. Pass a URL to the pd.read_csv Method.mp4 20.8 MB
  • 11. Working with Dates and Times in Datasets/6. Create Range of Dates with the pd.date_range() Method, Part 1.mp4 20.7 MB
  • 5. DataFrames II Filtering Data/8. Check for Duplicate DataFrame Rows with the duplicated Method.mp4 20.5 MB
  • 11. Working with Dates and Times in Datasets/17. Timedeltas in a Dataset.mp4 20.5 MB
  • 4. DataFrames I Introduction/11. Drop DataFrame Rows with Null Values with the dropna Method.mp4 20.1 MB
  • 8. MultiIndex/4. Change Index Level Name with the set_names Method.mp4 19.9 MB
  • 11. Working with Dates and Times in Datasets/7. Create Range of Dates with the pd.date_range() Method, Part 2.mp4 19.4 MB
  • 3. Series/7. Parameters and Arguments.mp4 19.2 MB
  • 4. DataFrames I Introduction/9. Broadcasting Operations on DataFrames.mp4 19.1 MB
  • 3. Series/2. Create A Series Object from a Python List.mp4 19.0 MB
  • 10. Merging, Joining, and Concatenating DataFrames/4. Inner Joins, Part 1.mp4 18.8 MB
  • 1. Installation and Setup/9. Windows - Download the Anaconda Distribution.mp4 18.7 MB
  • 10. Merging, Joining, and Concatenating DataFrames/5. Inner Joins, Part 2.mp4 18.6 MB
  • 5. DataFrames II Filtering Data/9. Delete Duplicate DataFrame Rows with the drop_duplicates Method.mp4 18.4 MB
  • 7. Working with Text Data/7. Split Strings by Characters with the str.split Method.mp4 18.4 MB
  • 8. MultiIndex/15. Use the pd.melt method to create a narrow dataset from a wide one.mp4 18.1 MB
  • 4. DataFrames I Introduction/8. Add New Column to DataFrame.mp4 18.1 MB
  • 1. Installation and Setup/16. Popular Keyboard Shortcuts in Jupyter Notebook.mp4 17.8 MB
  • 5. DataFrames II Filtering Data/7. Check For Inclusion Within a Range of Values with the between Method.mp4 17.6 MB
  • 5. DataFrames II Filtering Data/4. Filter DataFrame with More than One Condition (OR - ).mp4 17.6 MB
  • 11. Working with Dates and Times in Datasets/2. Review of Python's datetime Module.mp4 17.5 MB
  • 11. Working with Dates and Times in Datasets/8. Create Range of Dates with the pd.date_range() Method, Part 3.mp4 17.1 MB
  • 6. DataFrames III Data Extraction/9. Delete Rows or Columns from a DataFrame.mp4 17.0 MB
  • 1. Installation and Setup/4. MacOS - Download the Anaconda Distribution, our Python development environment.mp4 17.0 MB
  • 7. Working with Text Data/3. Use the str.replace method to replace all occurrences of character with another.mp4 16.8 MB
  • 13. Visualization/1. Intro to Visualization Section.mp4 16.6 MB
  • 7. Working with Text Data/4. Filter a DataFrame's Rows with String Methods.mp4 16.3 MB
  • 6. DataFrames III Data Extraction/16. Create a Copy of a DataFrame with the copy Method.mp4 16.2 MB
  • 7. Working with Text Data/9. Exploring the expand and n Parameters of the str.split Method.mp4 16.0 MB
  • 7. Working with Text Data/2. Common String Methods - lower, upper, title, and len.mp4 15.6 MB
  • 4. DataFrames I Introduction/4. Select One Column from a DataFrame.mp4 15.6 MB
  • 8. MultiIndex/11. The .unstack() Method, Part 2.mp4 15.2 MB
  • 2. BONUS Python Crash Course/1. Intro to the Python Crash Course.mp4 15.1 MB
  • 8. MultiIndex/8. The .swaplevel() Method.mp4 15.0 MB
  • 9. The GroupBy Object/1. Intro to the Groupby Module.mp4 15.0 MB
  • 11. Working with Dates and Times in Datasets/1. Intro to the Working with Dates and Times Module.mp4 14.8 MB
  • 14. Options and Settings in pandas/3. Changing pandas Options with Methods.mp4 14.6 MB
  • 11. Working with Dates and Times in Datasets/9. The .dt Accessor.mp4 14.3 MB
  • 6. DataFrames III Data Extraction/12. Filter A DataFrame with the where method.mp4 14.2 MB
  • 6. DataFrames III Data Extraction/15. Apply a Function to every DataFrame Row with the apply Method.mp4 14.1 MB
  • 4. DataFrames I Introduction/15. Sort a DataFrame with the sort_values Method, Part I.mp4 13.9 MB
  • 8. MultiIndex/9. The .stack() Method.mp4 13.8 MB
  • 9. The GroupBy Object/6. The .agg() Method.mp4 13.8 MB
  • 4. DataFrames I Introduction/19. Rank Series Values with the rank Method.mp4 13.8 MB
  • 4. DataFrames I Introduction/3. Differences between Shared Methods.mp4 13.7 MB
  • 3. Series/26. The Series#map Method.mp4 13.7 MB
  • 3. Series/5. Intro to Attributes on a Series Object.mp4 13.5 MB
  • 11. Working with Dates and Times in Datasets/3. The pandas Timestamp Object.mp4 13.4 MB
  • 5. DataFrames II Filtering Data/5. Check for Inclusion with the isin Method.mp4 13.1 MB
  • 3. Series/25. Use the apply Method to Invoke a Function on Every Series Values.mp4 12.9 MB
  • 5. DataFrames II Filtering Data/6. Check for Null and Present DataFrame Values with the isnull and notnull Methods.mp4 12.9 MB
  • 8. MultiIndex/13. The pivot Method.mp4 12.7 MB
  • 6. DataFrames III Data Extraction/11. Use the nsmallest nlargest methods to get rows with smallest largest values..mp4 12.7 MB
  • 8. MultiIndex/12. The .unstack() Method, Part 3.mp4 12.6 MB
  • 7. Working with Text Data/8. More Practice with the str.split method on a Series.mp4 12.5 MB
  • 6. DataFrames III Data Extraction/14. A Review of the apply Method on a pandas Series Object.mp4 12.3 MB
  • 3. Series/12. Accessing More Series Attributes.mp4 12.2 MB
  • 7. Working with Text Data/6. Invoke String Methods on DataFrame Index and Columns.mp4 11.7 MB
  • 3. Series/13. Use the sort_values method to sort a Series in ascending or descending order.mp4 11.4 MB
  • 4. DataFrames I Introduction/13. Fill in Null DataFrame Values with the fillna Method.mp4 11.3 MB
  • 9. The GroupBy Object/5. Grouping by Multiple Columns.mp4 10.9 MB
  • 3. Series/22. Math Methods on Series Objects.mp4 10.7 MB
  • 9. The GroupBy Object/3. Retrieve a group from a GroupBy object with the get_group Method.mp4 10.6 MB
  • 4. DataFrames I Introduction/6. Select Two or More Columns from a DataFrame.mp4 10.4 MB
  • 3. Series/11. Passing pandas Objects to Python Built-In Functions.mp4 10.4 MB
  • 11. Working with Dates and Times in Datasets/4. The pandas DateTimeIndex Object.mp4 10.1 MB
  • 7. Working with Text Data/5. More DataFrame String Methods - strip, lstrip, and rstrip.mp4 10.0 MB
  • 3. Series/14. Use the inplace Parameter to permanently mutate a pandas data structure.mp4 9.9 MB
  • 6. DataFrames III Data Extraction/10. Create Random Sample with the sample Method.mp4 9.8 MB
  • 5. DataFrames II Filtering Data/3. Filter DataFrame with More than One Condition (AND - &).mp4 9.8 MB
  • 2. BONUS Python Crash Course/2. Comments.mp4 9.6 MB
  • 3. Series/18. Extract Series Values by Index Positiox.mp4 9.3 MB
  • 4. DataFrames I Introduction/16. Sort a DataFrame with the sort_values Method, Part II.mp4 9.3 MB
  • 1. Installation and Setup/15. Code Cell Execution in Jupyter Notebook.mp4 9.2 MB
  • 3. Series/15. Use the sort_index Method to Sort the Index of a pandas Series object.mp4 9.0 MB
  • 8. MultiIndex/10. The .unstack() Method, Part 1.mp4 8.9 MB
  • 4. DataFrames I Introduction/10. A Review of the value_counts Method.mp4 8.8 MB
  • 5. DataFrames II Filtering Data/10. Identify and Count Unique Values with the unique and nunique Methods.mp4 8.6 MB
  • 3. Series/6. Intro to Methods on a Series Object.mp4 8.3 MB
  • 3. Series/17. Use Python's in Keyword to Check for Inclusion in Series values or index.mp4 7.7 MB
  • 3. Series/1. Create Jupyter Notebook for the Series Module.mp4 7.5 MB
  • 10. Merging, Joining, and Concatenating DataFrames/11. The pd.merge() Method.mp4 7.2 MB
  • 3. Series/24. Use the value_counts Method to See Counts of Unique Values within a Series.mp4 7.1 MB
  • 4. DataFrames I Introduction/18. Sort DataFrame Indexwith the sort_index Method.mp4 6.9 MB
  • 3. Series/10. Use the head and tail Methods to Return Rows from Beginning and End of Dataset.mp4 6.8 MB
  • 10. Merging, Joining, and Concatenating DataFrames/10. The .join() Method.mp4 6.6 MB
  • 14. Options and Settings in pandas/4. The precision Option.mp4 6.4 MB
  • 3. Series/23. Use the idxmax and idxmin Methods to Find Index of Greatest or Smallest Value.mp4 6.0 MB
  • 12. Input and Output in pandas/1. Intro to the Input and Output Section.mp4 5.8 MB
  • 3. Series/3. Create A Series Object from a Python Dictionary.mp4 5.5 MB
  • 14. Options and Settings in pandas/1. Introduction to the Options and Settings Module.mp4 3.5 MB
  • 15. Conclusion/1. Conclusion.mp4 3.1 MB
  • 1. Installation and Setup/12.1 pandas.zip 702.7 kB
  • 1. Installation and Setup/1.1 pandas.zip 701.2 kB
  • 1. Installation and Setup/8.1 pandas.zip 701.2 kB
  • 1. Installation and Setup/3.1 notebooks.zip 286.6 kB
  • 2. BONUS Python Crash Course/8. String Methods.srt 32.7 kB
  • 1. Installation and Setup/11. Windows - Create conda Environment and Install pandas and Jupyter Notebook.srt 30.3 kB
  • 2. BONUS Python Crash Course/7. Custom Functions.srt 26.6 kB
  • 5. DataFrames II Filtering Data/1. This Module's Dataset + Memory Optimization.srt 25.4 kB
  • 2. BONUS Python Crash Course/4. Operators.srt 24.9 kB
  • 2. BONUS Python Crash Course/11. Dictionaries.srt 24.5 kB
  • 2. BONUS Python Crash Course/10. Index Positions and Slicing.srt 24.2 kB
  • 3. Series/8. Create Series from Dataset with the pd.read_csv Method.srt 23.8 kB
  • 1. Installation and Setup/12. Windows - Unpack Course Materials + The Startdown and Shutdown Process.srt 21.9 kB
  • 1. Installation and Setup/8. MacOS - Unpack Course Materials + The Start and Shutdown Process.srt 21.8 kB
  • 1. Installation and Setup/7. MacOS - Create conda Environment and Install pandas and Jupyter Notebook.srt 21.8 kB
  • 4. DataFrames I Introduction/2. Shared Methods and Attributes between Series and DataFrames.srt 21.3 kB
  • 2. BONUS Python Crash Course/9. Lists.srt 20.9 kB
  • 1. Installation and Setup/1. Introduction to Data Analysis with Pandas and Python.srt 20.8 kB
  • 6. DataFrames III Data Extraction/3. Retrieve Rows by Index Label with loc Accessor.srt 19.7 kB
  • 11. Working with Dates and Times in Datasets/15. Timeseries Offsets.srt 19.4 kB
  • 5. DataFrames II Filtering Data/2. Filter a DataFrame Based on A Condition.srt 19.1 kB
  • 10. Merging, Joining, and Concatenating DataFrames/6. Outer Joins.srt 18.2 kB
  • 2. BONUS Python Crash Course/6. Built-in Functions.srt 17.3 kB
  • 2. BONUS Python Crash Course/3. Basic Data Types.srt 17.3 kB
  • 11. Working with Dates and Times in Datasets/6. Create Range of Dates with the pd.date_range() Method, Part 1.srt 17.2 kB
  • 11. Working with Dates and Times in Datasets/12. Selecting Rows from a DataFrame with a DateTimeIndex.srt 17.2 kB
  • 3. Series/2. Create A Series Object from a Python List.srt 16.9 kB
  • 8. MultiIndex/14. Use the pivot_table method to create an aggregate summary of a DataFrame.srt 16.9 kB
  • 8. MultiIndex/6. Extract Rows from a MultiIndex DataFrame.srt 16.6 kB
  • 11. Working with Dates and Times in Datasets/5. The pd.to_datetime() Method.srt 16.4 kB
  • 4. DataFrames I Introduction/14. Convert DataFrame Column Types with the astype Method.srt 15.8 kB
  • 10. Merging, Joining, and Concatenating DataFrames/9. Merging by Indexes with the left_index and right_index Parameters.srt 15.8 kB
  • 3. Series/19. Extract Series Values by Index Label.srt 15.7 kB
  • 1. Installation and Setup/13. Intro to the Jupyter Notebook Interface.srt 15.6 kB
  • 11. Working with Dates and Times in Datasets/13. Timestamp Object Attributes and Methods.srt 15.4 kB
  • 4. DataFrames I Introduction/1. Intro to DataFrames I Module.srt 15.3 kB
  • 3. Series/7. Parameters and Arguments.srt 15.0 kB
  • 10. Merging, Joining, and Concatenating DataFrames/4. Inner Joins, Part 1.srt 14.9 kB
  • 11. Working with Dates and Times in Datasets/17. Timedeltas in a Dataset.srt 14.7 kB
  • 8. MultiIndex/2. Create a MultiIndex on a DataFrame with the set_index Method.srt 14.6 kB
  • 9. The GroupBy Object/2. First Operations with groupby Object.srt 14.3 kB
  • 12. Input and Output in pandas/6. Import Excel File into pandas with the read_excel Method.srt 14.1 kB
  • 5. DataFrames II Filtering Data/8. Check for Duplicate DataFrame Rows with the duplicated Method.srt 14.0 kB
  • 6. DataFrames III Data Extraction/8. Rename Index Labels or Columns in a DataFrame.srt 14.0 kB
  • 3. Series/21. Use the get Method to Retrieve a Value for an index label in a Series.srt 14.0 kB
  • 1. Installation and Setup/6. MacOS - Access the Terminal Application.srt 14.0 kB
  • 4. DataFrames I Introduction/9. Broadcasting Operations on DataFrames.srt 13.8 kB
  • 10. Merging, Joining, and Concatenating DataFrames/7. Left Joins.srt 13.8 kB
  • 10. Merging, Joining, and Concatenating DataFrames/5. Inner Joins, Part 2.srt 13.6 kB
  • 10. Merging, Joining, and Concatenating DataFrames/8. The left_on and right_on Parameters.srt 13.6 kB
  • 11. Working with Dates and Times in Datasets/2. Review of Python's datetime Module.srt 13.5 kB
  • 13. Visualization/2. Use the plot Method to Render a Line Chart.srt 13.1 kB
  • 9. The GroupBy Object/7. Iterating through Groups.srt 13.0 kB
  • 2. BONUS Python Crash Course/5. Variables.srt 13.0 kB
  • 9. The GroupBy Object/4. Methods on the Groupby Object and DataFrame Columns.srt 13.0 kB
  • 11. Working with Dates and Times in Datasets/7. Create Range of Dates with the pd.date_range() Method, Part 2.srt 12.9 kB
  • 7. Working with Text Data/7. Split Strings by Characters with the str.split Method.srt 12.9 kB
  • 6. DataFrames III Data Extraction/13. Filter A DataFrame with the query method.srt 12.9 kB
  • 1. Installation and Setup/5. MacOS - Install Anaconda Distribution.srt 12.8 kB
  • 11. Working with Dates and Times in Datasets/16. The Timedelta Object.srt 12.8 kB
  • 1. Installation and Setup/17. Import Libraries into Jupyter Notebook.srt 12.8 kB
  • 5. DataFrames II Filtering Data/9. Delete Duplicate DataFrame Rows with the drop_duplicates Method.srt 12.7 kB
  • 11. Working with Dates and Times in Datasets/11. Import Financial Data Set with pandas_datareader Library.srt 12.7 kB
  • 9. The GroupBy Object/1. Intro to the Groupby Module.srt 12.5 kB
  • 5. DataFrames II Filtering Data/4. Filter DataFrame with More than One Condition (OR - ).srt 12.4 kB
  • 8. MultiIndex/5. The sort_index Method on a MultiIndex DataFrame.srt 12.4 kB
  • 8. MultiIndex/7. The transpose Method on a MultiIndex DataFrame.srt 12.3 kB
  • 7. Working with Text Data/3. Use the str.replace method to replace all occurrences of character with another.srt 12.3 kB
  • 4. DataFrames I Introduction/4. Select One Column from a DataFrame.srt 12.3 kB
  • 6. DataFrames III Data Extraction/5. Passing second arguments to the loc and iloc Accessors.srt 12.2 kB
  • 12. Input and Output in pandas/7. Export Excel File with the to_excel Method.srt 12.2 kB
  • 4. DataFrames I Introduction/8. Add New Column to DataFrame.srt 12.0 kB
  • 14. Options and Settings in pandas/2. Changing pandas Options with Attributes and Dot Syntax.srt 12.0 kB
  • 3. Series/5. Intro to Attributes on a Series Object.srt 11.4 kB
  • 8. MultiIndex/13. The pivot Method.srt 11.2 kB
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