11. Import Financial Data Set with pandas_datareader Library.mp4 (25.5 MB)
12. Selecting Rows from a DataFrame with a DateTimeIndex.mp4 (18.3 MB)
13. Timestamp Object Attributes.mp4 (19.6 MB)
14. The .truncate() Method.mp4 (9.0 MB)
15. pd.DateOffset Objects.mp4 (25.6 MB)
16. More Fun with pd.DateOffset Objects.mp4 (31.9 MB)
17. The pandas Timedelta Object.mp4 (15.4 MB)
18. Timedeltas in a Dataset.mp4 (19.6 MB)
2. Review of Python's datetime Module.mp4 (16.7 MB)
3. The pandas Timestamp Object.mp4 (12.8 MB)
4. The pandas DateTimeIndex Object.mp4 (9.7 MB)
5. The pd.to_datetime() Method.mp4 (22.9 MB)
6. Create Range of Dates with the pd.date_range() Method, Part 1.mp4 (19.7 MB)
7. Create Range of Dates with the pd.date_range() Method, Part 2.mp4 (18.5 MB)
8. Create Range of Dates with the pd.date_range() Method, Part 3.mp4 (16.3 MB)
9. The .dt Accessor.mp4 (13.7 MB)
11. Panels
1. Intro to the Module + Fetch Panel Dataset from Google Finance.mp4 (13.7 MB)
10. The .swapaxes() Method.mp4 (9.7 MB)
11. A Review of the Panels Module.html (0.1 KB)
2. The Axes of a Panel Object.mp4 (16.3 MB)
3. Panel Attributes.mp4 (10.5 MB)
4. Use Bracket Notation to Extract a DataFrame from a Panel.mp4 (8.3 MB)
5. Extracting with the .loc, .iloc, and .ix Methods.mp4 (13.5 MB)
6. Convert Panel to a MultiIndex DataFrame (and Vice Versa).mp4 (8.7 MB)
7. The .major_xs() Method.mp4 (12.1 MB)
8. The .minor_xs() Method.mp4 (13.6 MB)
9. Transpose a Panel with the .transpose() Method.mp4 (15.7 MB)
12. Input and Output
1. Intro to the Input and Output Module.mp4 (2.8 MB)
2. Feed pd.read_csv() Method a URL Argument.mp4 (7.6 MB)
3. Quick Object Conversions.mp4 (11.4 MB)
4. Export DataFrame to CSV File with the .to_csv() Method.mp4 (10.7 MB)
5. Install xlrd and openpyxl Libraries to Read and Write Excel Files.mp4 (6.0 MB)
6. Import Excel File into pandas.mp4 (19.1 MB)
7. Export Excel File.mp4 (17.8 MB)
8. Input and Output.html (0.1 KB)
13. Visualization
1. Intro to Visualization Module.mp4 (7.3 MB)
2. The .plot() Method.mp4 (19.0 MB)
3. Modifying Aesthetics with Templates.mp4 (12.1 MB)
4. Bar Graphs.mp4 (12.3 MB)
5. Pie Charts.mp4 (9.9 MB)
6. Histograms.mp4 (12.2 MB)
7. Visualization.html (0.1 KB)
14. Options and Settings
1. Introduction to the Options and Settings Module.mp4 (3.3 MB)
2. Changing pandas Options with Attributes and Dot Syntax.mp4 (19.8 MB)
3. Changing pandas Options with Methods.mp4 (13.9 MB)
4. The precision Option.mp4 (6.1 MB)
15. Conclusion
1. Conclusion.mp4 (3.0 MB)
2. Series
1. Create Jupyter Notebook for the Series Module.mp4 (3.8 MB)
10. More Series Attributes.mp4 (11.7 MB)
11. The .sort_values() Method.mp4 (10.8 MB)
11.1 Official pandas Documentation.html (0.1 KB)
12. The inplace Parameter.mp4 (9.4 MB)
13. The .sort_index() Method.mp4 (8.6 MB)
13.1 Official pandas Documentation.html (0.1 KB)
14. Python's in Keyword.mp4 (7.3 MB)
15. Extract Series Values by Index Position.mp4 (8.9 MB)
16. Extract Series Values by Index Label.mp4 (13.7 MB)
17. The .get() Method on a Series.mp4 (9.6 MB)
18. Math Methods on Series Objects.mp4 (10.2 MB)
19. The .idxmax() and .idxmin() Methods.mp4 (5.8 MB)
2. Create A Series Object from a Python List.mp4 (18.1 MB)
20. The .value_counts() Method.mp4 (6.7 MB)
21. The .apply() Method.mp4 (12.3 MB)
22. The .map() Method.mp4 (13.1 MB)
23. A Review of the Series Module.html (0.1 KB)
3. Create A Series Object from a Python Dictionary.mp4 (5.2 MB)
4. Intro to Attributes.mp4 (12.9 MB)
5. Intro to Methods.mp4 (7.9 MB)
6. Parameters and Arguments.mp4 (18.3 MB)
7. Import Series with the .read_csv() Method.mp4 (21.1 MB)
8. The .head() and .tail() Methods.mp4 (6.5 MB)
8.1 Official pandas Documentation.html (0.1 KB)
9. Python Built-In Functions.mp4 (9.9 MB)
3. DataFrames I
1. Intro to Data
Description
Udemy - Data Analysis with Pandas and Python
Welcome to the most comprehensive Pandas course available on Udemy! An excellent choice for both beginners and experts looking to expand their knowledge on one of the most popular Python libraries in the world!
