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[FreeCourseSite.com] Udemy - Data Analysis with Pandas and Python
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2021-1-26 17:45
2024-11-21 13:16
210
4.16 GB
166
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Udemy
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Data
Analysis
with
Pandas
and
Python
文件列表
1. Installation and Setup/1. Introduction to Data Analysis with Pandas and Python.mp4
34MB
1. Installation and Setup/10. Windows - Install Anaconda Distribution.mp4
38.65MB
1. Installation and Setup/11. Windows - Create conda Environment and Install pandas and Jupyter Notebook.mp4
111.78MB
1. Installation and Setup/12. Windows - Unpack Course Materials + The Startdown and Shutdown Process.mp4
47.43MB
1. Installation and Setup/13. Intro to the Jupyter Notebook Interface.mp4
33.27MB
1. Installation and Setup/14. Cell Types and Cell Modes in Jupyter Notebook.mp4
19.96MB
1. Installation and Setup/15. Code Cell Execution in Jupyter Notebook.mp4
8.81MB
1. Installation and Setup/16. Popular Keyboard Shortcuts in Jupyter Notebook.mp4
17MB
1. Installation and Setup/17. Import Libraries into Jupyter Notebook.mp4
25.83MB
1. Installation and Setup/2. About Me.mp4
21.3MB
1. Installation and Setup/4. MacOS - Download the Anaconda Distribution, our Python development environment.mp4
16.22MB
1. Installation and Setup/5. MacOS - Install Anaconda Distribution.mp4
90.99MB
1. Installation and Setup/6. MacOS - Access the Terminal Application.mp4
73.07MB
1. Installation and Setup/7. MacOS - Create conda Environment and Install pandas and Jupyter Notebook.mp4
112.47MB
1. Installation and Setup/8. MacOS - Unpack Course Materials + The Start and Shutdown Process.mp4
110.84MB
1. Installation and Setup/9. Windows - Download the Anaconda Distribution.mp4
17.87MB
10. Merging, Joining, and Concatenating DataFrames/1. Intro to the Merging, Joining, and Concatenating Section.mp4
20.99MB
10. Merging, Joining, and Concatenating DataFrames/10. The .join() Method.mp4
6.27MB
10. Merging, Joining, and Concatenating DataFrames/11. The pd.merge() Method.mp4
6.85MB
10. Merging, Joining, and Concatenating DataFrames/2. The pd.concat Method, Part 1.mp4
21.79MB
10. Merging, Joining, and Concatenating DataFrames/3. The pd.concat Method, Part 2.mp4
30.59MB
10. Merging, Joining, and Concatenating DataFrames/4. Inner Joins, Part 1.mp4
17.92MB
10. Merging, Joining, and Concatenating DataFrames/5. Inner Joins, Part 2.mp4
17.75MB
10. Merging, Joining, and Concatenating DataFrames/6. Outer Joins.mp4
25.94MB
10. Merging, Joining, and Concatenating DataFrames/7. Left Joins.mp4
20.99MB
10. Merging, Joining, and Concatenating DataFrames/8. The left_on and right_on Parameters.mp4
20.25MB
10. Merging, Joining, and Concatenating DataFrames/9. Merging by Indexes with the left_index and right_index Parameters.mp4
22.7MB
11. Working with Dates and Times in Datasets/1. Intro to the Working with Dates and Times Module.mp4
14.11MB
11. Working with Dates and Times in Datasets/10. Install pandas-datareader Library.mp4
32.99MB
11. Working with Dates and Times in Datasets/11. Import Financial Data Set with pandas_datareader Library.mp4
41.66MB
11. Working with Dates and Times in Datasets/12. Selecting Rows from a DataFrame with a DateTimeIndex.mp4
74.26MB
11. Working with Dates and Times in Datasets/13. Timestamp Object Attributes and Methods.mp4
54.13MB
11. Working with Dates and Times in Datasets/14. The pd.DateOffset Object.mp4
43.83MB
11. Working with Dates and Times in Datasets/15. Timeseries Offsets.mp4
74.55MB
11. Working with Dates and Times in Datasets/16. The Timedelta Object.mp4
32.25MB
11. Working with Dates and Times in Datasets/17. Timedeltas in a Dataset.mp4
19.55MB
11. Working with Dates and Times in Datasets/2. Review of Python's datetime Module.mp4
16.74MB
11. Working with Dates and Times in Datasets/3. The pandas Timestamp Object.mp4
12.81MB
11. Working with Dates and Times in Datasets/4. The pandas DateTimeIndex Object.mp4
9.65MB
11. Working with Dates and Times in Datasets/5. The pd.to_datetime() Method.mp4
22.88MB
11. Working with Dates and Times in Datasets/6. Create Range of Dates with the pd.date_range() Method, Part 1.mp4
19.68MB
11. Working with Dates and Times in Datasets/7. Create Range of Dates with the pd.date_range() Method, Part 2.mp4
18.55MB
11. Working with Dates and Times in Datasets/8. Create Range of Dates with the pd.date_range() Method, Part 3.mp4
16.34MB
11. Working with Dates and Times in Datasets/9. The .dt Accessor.mp4
13.69MB
12. Input and Output in pandas/1. Intro to the Input and Output Section.mp4
5.52MB
12. Input and Output in pandas/2. Pass a URL to the pd.read_csv Method.mp4
19.83MB
12. Input and Output in pandas/3. Quick Object Conversions.mp4
43.65MB
12. Input and Output in pandas/4. Export CSV File with the to_csv Method.mp4
27.23MB
12. Input and Output in pandas/5. Install xlrd and openpyxl Libraries to Read and Write Excel Files.mp4
40.14MB
12. Input and Output in pandas/6. Import Excel File into pandas with the read_excel Method.mp4
49.2MB
12. Input and Output in pandas/7. Export Excel File with the to_excel Method.mp4
46.97MB
13. Visualization/1. Intro to Visualization Section.mp4
15.79MB
13. Visualization/2. Use the plot Method to Render a Line Chart.mp4
33.33MB
13. Visualization/3. Modifying Plot Aesthetics with matplotlib Templates.mp4
23.91MB
13. Visualization/4. Creating Bar Graphs to Show Counts.mp4
27.23MB
13. Visualization/5. Creating Pie Charts to Represent Proportions.mp4
21.44MB
14. Options and Settings in pandas/1. Introduction to the Options and Settings Module.mp4
3.33MB
14. Options and Settings in pandas/2. Changing pandas Options with Attributes and Dot Syntax.mp4
19.84MB
14. Options and Settings in pandas/3. Changing pandas Options with Methods.mp4
13.93MB
14. Options and Settings in pandas/4. The precision Option.mp4
6.11MB
15. Conclusion/1. Conclusion.mp4
2.95MB
2. BONUS Python Crash Course/1. Intro to the Python Crash Course.mp4
14.4MB
2. BONUS Python Crash Course/10. Index Positions and Slicing.mp4
55.64MB
2. BONUS Python Crash Course/11. Dictionaries.mp4
53.76MB
2. BONUS Python Crash Course/2. Comments.mp4
9.18MB
2. BONUS Python Crash Course/3. Basic Data Types.mp4
32.46MB
2. BONUS Python Crash Course/4. Operators.mp4
50.67MB
2. BONUS Python Crash Course/5. Variables.mp4
24.01MB
2. BONUS Python Crash Course/6. Built-in Functions.mp4
32.96MB
2. BONUS Python Crash Course/7. Custom Functions.mp4
56.46MB
2. BONUS Python Crash Course/8. String Methods.mp4
74.71MB
2. BONUS Python Crash Course/9. Lists.mp4
44.53MB
3. Series/1. Create Jupyter Notebook for the Series Module.mp4
7.19MB
3. Series/10. Use the head and tail Methods to Return Rows from Beginning and End of Dataset.mp4
6.47MB
3. Series/11. Passing pandas Objects to Python Built-In Functions.mp4
9.87MB
3. Series/12. Accessing More Series Attributes.mp4
11.66MB
3. Series/13. Use the sort_values method to sort a Series in ascending or descending order.mp4
10.84MB
3. Series/14. Use the inplace Parameter to permanently mutate a pandas data structure.mp4
9.39MB
3. Series/15. Use the sort_index Method to Sort the Index of a pandas Series object.mp4
8.58MB
3. Series/17. Use Python's in Keyword to Check for Inclusion in Series values or index.mp4
7.31MB
3. Series/18. Extract Series Values by Index Positiox.mp4
8.91MB
3. Series/19. Extract Series Values by Index Label.mp4
46.24MB
3. Series/2. Create A Series Object from a Python List.mp4
18.12MB
3. Series/21. Use the get Method to Retrieve a Value for an index label in a Series.mp4
41.11MB
3. Series/22. Math Methods on Series Objects.mp4
10.16MB
3. Series/23. Use the idxmax and idxmin Methods to Find Index of Greatest or Smallest Value.mp4
5.75MB
3. Series/24. Use the value_counts Method to See Counts of Unique Values within a Series.mp4
6.73MB
3. Series/25. Use the apply Method to Invoke a Function on Every Series Values.mp4
12.32MB
3. Series/26. The Series#map Method.mp4
13.1MB
3. Series/3. Create A Series Object from a Python Dictionary.mp4
5.19MB
3. Series/5. Intro to Attributes on a Series Object.mp4
12.86MB
3. Series/6. Intro to Methods on a Series Object.mp4
7.92MB
3. Series/7. Parameters and Arguments.mp4
18.28MB
3. Series/8. Create Series from Dataset with the pd.read_csv Method.mp4
60.35MB
4. DataFrames I Introduction/1. Intro to DataFrames I Module.mp4
49.79MB
4. DataFrames I Introduction/10. A Review of the value_counts Method.mp4
8.43MB
4. DataFrames I Introduction/11. Drop DataFrame Rows with Null Values with the dropna Method.mp4
19.21MB
4. DataFrames I Introduction/13. Fill in Null DataFrame Values with the fillna Method.mp4
10.75MB
4. DataFrames I Introduction/14. Convert DataFrame Column Types with the astype Method.mp4
23.86MB
4. DataFrames I Introduction/15. Sort a DataFrame with the sort_values Method, Part I.mp4
13.28MB
4. DataFrames I Introduction/16. Sort a DataFrame with the sort_values Method, Part II.mp4
8.83MB
4. DataFrames I Introduction/18. Sort DataFrame Indexwith the sort_index Method.mp4
6.57MB
4. DataFrames I Introduction/19. Rank Series Values with the rank Method.mp4
13.17MB
4. DataFrames I Introduction/2. Shared Methods and Attributes between Series and DataFrames.mp4
67.52MB
4. DataFrames I Introduction/3. Differences between Shared Methods.mp4
13.11MB
4. DataFrames I Introduction/4. Select One Column from a DataFrame.mp4
14.88MB
4. DataFrames I Introduction/6. Select Two or More Columns from a DataFrame.mp4
9.93MB
4. DataFrames I Introduction/8. Add New Column to DataFrame.mp4
17.23MB
4. DataFrames I Introduction/9. Broadcasting Operations on DataFrames.mp4
18.23MB
5. DataFrames II Filtering Data/1. This Module's Dataset + Memory Optimization.mp4
97.89MB
5. DataFrames II Filtering Data/10. Identify and Count Unique Values with the unique and nunique Methods.mp4
8.2MB
5. DataFrames II Filtering Data/2. Filter a DataFrame Based on A Condition.mp4
27.4MB
5. DataFrames II Filtering Data/3. Filter DataFrame with More than One Condition (AND - &).mp4
9.3MB
5. DataFrames II Filtering Data/4. Filter DataFrame with More than One Condition (OR - ).mp4
16.76MB
5. DataFrames II Filtering Data/5. Check for Inclusion with the isin Method.mp4
12.53MB
5. DataFrames II Filtering Data/6. Check for Null and Present DataFrame Values with the isnull and notnull Methods.mp4
12.26MB
5. DataFrames II Filtering Data/7. Check For Inclusion Within a Range of Values with the between Method.mp4
16.77MB
5. DataFrames II Filtering Data/8. Check for Duplicate DataFrame Rows with the duplicated Method.mp4
19.56MB
5. DataFrames II Filtering Data/9. Delete Duplicate DataFrame Rows with the drop_duplicates Method.mp4
17.55MB
6. DataFrames III Data Extraction/1. Intro to the DataFrames III Module + Import Dataset.mp4
23.37MB
6. DataFrames III Data Extraction/10. Create Random Sample with the sample Method.mp4
9.33MB
6. DataFrames III Data Extraction/11. Use the nsmallest nlargest methods to get rows with smallest largest values..mp4
12.07MB
6. DataFrames III Data Extraction/12. Filter A DataFrame with the where method.mp4
13.56MB
6. DataFrames III Data Extraction/13. Filter A DataFrame with the query method.mp4
19.92MB
6. DataFrames III Data Extraction/14. A Review of the apply Method on a pandas Series Object.mp4
11.75MB
6. DataFrames III Data Extraction/15. Apply a Function to every DataFrame Row with the apply Method.mp4
13.41MB
6. DataFrames III Data Extraction/16. Create a Copy of a DataFrame with the copy Method.mp4
15.44MB
6. DataFrames III Data Extraction/2. Use the set_index and reset_index methods to define a new DataFrame index.mp4
39.21MB
6. DataFrames III Data Extraction/3. Retrieve Rows by Index Label with loc Accessor.mp4
61.12MB
6. DataFrames III Data Extraction/4. Retrieve Rows by Index Position with iloc Accessor.mp4
39.56MB
6. DataFrames III Data Extraction/5. Passing second arguments to the loc and iloc Accessors.mp4
45.85MB
6. DataFrames III Data Extraction/6. Set New Value for a Specific Cell or Cells In a Row.mp4
19.94MB
6. DataFrames III Data Extraction/7. Set Multiple Values in a DataFrame.mp4
38.56MB
6. DataFrames III Data Extraction/8. Rename Index Labels or Columns in a DataFrame.mp4
58.06MB
6. DataFrames III Data Extraction/9. Delete Rows or Columns from a DataFrame.mp4
16.21MB
7. Working with Text Data/1. Intro to the Working with Text Data Section.mp4
32.29MB
7. Working with Text Data/2. Common String Methods - lower, upper, title, and len.mp4
14.89MB
7. Working with Text Data/3. Use the str.replace method to replace all occurrences of character with another.mp4
16MB
7. Working with Text Data/4. Filter a DataFrame's Rows with String Methods.mp4
15.55MB
7. Working with Text Data/5. More DataFrame String Methods - strip, lstrip, and rstrip.mp4
9.54MB
7. Working with Text Data/6. Invoke String Methods on DataFrame Index and Columns.mp4
11.13MB
7. Working with Text Data/7. Split Strings by Characters with the str.split Method.mp4
17.52MB
7. Working with Text Data/8. More Practice with the str.split method on a Series.mp4
11.92MB
7. Working with Text Data/9. Exploring the expand and n Parameters of the str.split Method.mp4
15.31MB
8. MultiIndex/1. Intro to the MultiIndex Module.mp4
19.97MB
8. MultiIndex/10. The .unstack() Method, Part 1.mp4
8.48MB
8. MultiIndex/11. The .unstack() Method, Part 2.mp4
14.53MB
8. MultiIndex/12. The .unstack() Method, Part 3.mp4
11.96MB
8. MultiIndex/13. The pivot Method.mp4
12.11MB
8. MultiIndex/14. Use the pivot_table method to create an aggregate summary of a DataFrame.mp4
22.16MB
8. MultiIndex/15. Use the pd.melt method to create a narrow dataset from a wide one.mp4
17.26MB
8. MultiIndex/2. Create a MultiIndex on a DataFrame with the set_index Method.mp4
45.69MB
8. MultiIndex/3. Extract Index Level Values with the get_level_values Method.mp4
20.66MB
8. MultiIndex/4. Change Index Level Name with the set_names Method.mp4
19.01MB
8. MultiIndex/5. The sort_index Method on a MultiIndex DataFrame.mp4
35.24MB
8. MultiIndex/6. Extract Rows from a MultiIndex DataFrame.mp4
47.01MB
8. MultiIndex/7. The transpose Method on a MultiIndex DataFrame.mp4
35.64MB
8. MultiIndex/8. The .swaplevel() Method.mp4
14.35MB
8. MultiIndex/9. The .stack() Method.mp4
13.19MB
9. The GroupBy Object/1. Intro to the Groupby Module.mp4
14.29MB
9. The GroupBy Object/2. First Operations with groupby Object.mp4
23.08MB
9. The GroupBy Object/3. Retrieve a group from a GroupBy object with the get_group Method.mp4
10.14MB
9. The GroupBy Object/4. Methods on the Groupby Object and DataFrame Columns.mp4
20.49MB
9. The GroupBy Object/5. Grouping by Multiple Columns.mp4
10.34MB
9. The GroupBy Object/6. The .agg() Method.mp4
13.18MB
9. The GroupBy Object/7. Iterating through Groups.mp4
21.37MB
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