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[DesireCourse.Net] Udemy - Data Analysis with Pandas and Python
magnet:?xt=urn:btih:05c6531ce6cdedb28ce8fa292571767cf4a2c240&dn=[DesireCourse.Net] Udemy - Data Analysis with Pandas and Python
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文件列表详情
05c6531ce6cdedb28ce8fa292571767cf4a2c240
infohash:
160
文件数量
3.77 GB
文件大小
2020-10-21 07:45
创建日期
2024-7-2 20:00
最后访问
相关分词
DesireCourse
Net
Udemy
-
Data
Analysis
with
Pandas
and
Python
1. Installation and Setup/1. Introduction to Data Analysis with Pandas and Python.mp4 34.01 MB
1. Installation and Setup/10. Windows - Install Anaconda Distribution.mp4 38.65 MB
1. Installation and Setup/11. Windows - Create conda Environment and Install pandas and Jupyter Notebook.mp4 111.79 MB
1. Installation and Setup/12. Windows - Unpack Course Materials + The Startdown and Shutdown Process.mp4 47.44 MB
1. Installation and Setup/13. Intro to the Jupyter Notebook Interface.mp4 33.27 MB
1. Installation and Setup/14. Cell Types and Cell Modes in Jupyter Notebook.mp4 19.96 MB
1. Installation and Setup/15. Code Cell Execution in Jupyter Notebook.mp4 8.82 MB
1. Installation and Setup/16. Popular Keyboard Shortcuts in Jupyter Notebook.mp4 17.01 MB
1. Installation and Setup/17. Import Libraries into Jupyter Notebook.mp4 25.84 MB
1. Installation and Setup/18. Python Crash Course, Part 1 - Data Types and Variables.mp4 11.99 MB
1. Installation and Setup/19. Python Crash Course, Part 2 - Lists.mp4 9.01 MB
1. Installation and Setup/2. About Me.mp4 21.31 MB
1. Installation and Setup/20. Python Crash Course, Part 3 - Dictionaries.mp4 7.21 MB
1. Installation and Setup/21. Python Crash Course, Part 4 - Operators.mp4 7.88 MB
1. Installation and Setup/22. Python Crash Course, Part 5 - Functions.mp4 10.13 MB
1. Installation and Setup/4. MacOS - Download the Anaconda Distribution, our Python development environment.mp4 16.23 MB
1. Installation and Setup/5. MacOS - Install Anaconda Distribution.mp4 91 MB
1. Installation and Setup/6. MacOS - Access the Terminal Application.mp4 73.08 MB
1. Installation and Setup/7. MacOS - Create conda Environment and Install pandas and Jupyter Notebook.mp4 112.47 MB
1. Installation and Setup/8. MacOS - Unpack Course Materials + The Start and Shutdown Process.mp4 110.84 MB
1. Installation and Setup/9. Windows - Download the Anaconda Distribution.mp4 17.88 MB
10. Working with Dates and Times in Datasets/1. Intro to the Working with Dates and Times Module.mp4 14.12 MB
10. Working with Dates and Times in Datasets/10. Install pandas-datareader Library.mp4 33 MB
10. Working with Dates and Times in Datasets/11. Import Financial Data Set with pandas_datareader Library.mp4 41.67 MB
10. Working with Dates and Times in Datasets/12. Selecting Rows from a DataFrame with a DateTimeIndex.mp4 74.27 MB
10. Working with Dates and Times in Datasets/13. Timestamp Object Attributes and Methods.mp4 54.13 MB
10. Working with Dates and Times in Datasets/14. The pd.DateOffset Object.mp4 43.83 MB
10. Working with Dates and Times in Datasets/15. Timeseries Offsets.mp4 74.55 MB
10. Working with Dates and Times in Datasets/16. The Timedelta Object.mp4 32.26 MB
10. Working with Dates and Times in Datasets/17. Timedeltas in a Dataset.mp4 19.56 MB
10. Working with Dates and Times in Datasets/2. Review of Python's datetime Module.mp4 16.74 MB
10. Working with Dates and Times in Datasets/3. The pandas Timestamp Object.mp4 12.81 MB
10. Working with Dates and Times in Datasets/4. The pandas DateTimeIndex Object.mp4 9.66 MB
10. Working with Dates and Times in Datasets/5. The pd.to_datetime() Method.mp4 22.89 MB
10. Working with Dates and Times in Datasets/6. Create Range of Dates with the pd.date_range() Method, Part 1.mp4 19.69 MB
10. Working with Dates and Times in Datasets/7. Create Range of Dates with the pd.date_range() Method, Part 2.mp4 18.55 MB
10. Working with Dates and Times in Datasets/8. Create Range of Dates with the pd.date_range() Method, Part 3.mp4 16.34 MB
10. Working with Dates and Times in Datasets/9. The .dt Accessor.mp4 13.69 MB
11. Input and Output in pandas/1. Intro to the Input and Output Section.mp4 5.53 MB
11. Input and Output in pandas/2. Pass a URL to the pd.read_csv Method.mp4 19.84 MB
11. Input and Output in pandas/3. Quick Object Conversions.mp4 43.65 MB
11. Input and Output in pandas/4. Export CSV File with the to_csv Method.mp4 27.24 MB
11. Input and Output in pandas/5. Install xlrd and openpyxl Libraries to Read and Write Excel Files.mp4 40.14 MB
11. Input and Output in pandas/6. Import Excel File into pandas with the read_excel Method.mp4 49.19 MB
11. Input and Output in pandas/7. Export Excel File with the to_excel Method.mp4 46.97 MB
12. Visualization/1. Intro to Visualization Section.mp4 15.8 MB
12. Visualization/2. Use the plot Method to Render a Line Chart.mp4 33.33 MB
12. Visualization/3. Modifying Plot Aesthetics with matplotlib Templates.mp4 23.91 MB
12. Visualization/4. Creating Bar Graphs to Show Counts.mp4 27.24 MB
12. Visualization/5. Creating Pie Charts to Represent Proportions.mp4 21.45 MB
13. Options and Settings in pandas/1. Introduction to the Options and Settings Module.mp4 3.33 MB
13. Options and Settings in pandas/2. Changing pandas Options with Attributes and Dot Syntax.mp4 19.84 MB
13. Options and Settings in pandas/3. Changing pandas Options with Methods.mp4 13.93 MB
13. Options and Settings in pandas/4. The precision Option.mp4 6.11 MB
14. Conclusion/1. Conclusion.mp4 2.96 MB
2. Series/1. Create Jupyter Notebook for the Series Module.mp4 7.19 MB
2. Series/10. Use the head and tail Methods to Return Rows from Beginning and End of Dataset.mp4 6.48 MB
2. Series/11. Passing pandas Objects to Python Built-In Functions.mp4 9.88 MB
2. Series/12. Accessing More Series Attributes.mp4 11.66 MB
2. Series/13. Use the sort_values method to sort a Series in ascending or descending order.mp4 10.84 MB
2. Series/14. Use the inplace Parameter to permanently mutate a pandas data structure.mp4 9.39 MB
2. Series/15. Use the sort_index Method to Sort the Index of a pandas Series object.mp4 8.57 MB
2. Series/17. Use Python's in Keyword to Check for Inclusion in Series values or index.mp4 7.31 MB
2. Series/18. Extract Series Values by Index Position.mp4 8.91 MB
2. Series/19. Extract Series Values by Index Label.mp4 46.25 MB
2. Series/2. Create A Series Object from a Python List.mp4 18.12 MB
2. Series/21. Use the get Method to Retrieve a Value for an index label in a Series.mp4 41.11 MB
2. Series/22. Math Methods on Series Objects.mp4 10.16 MB
2. Series/23. Use the idxmax and idxmin Methods to Find Index of Greatest or Smallest Value.mp4 5.76 MB
2. Series/24. Use the value_counts Method to See Counts of Unique Values within a Series.mp4 6.74 MB
2. Series/25. Use the apply Method to Invoke a Function on Every Series Values.mp4 12.32 MB
2. Series/26. The .map() Method.mp4 13.1 MB
2. Series/3. Create A Series Object from a Python Dictionary.mp4 5.2 MB
2. Series/5. Intro to Attributes on a Series Object.mp4 12.85 MB
2. Series/6. Intro to Methods on a Series Object.mp4 7.92 MB
2. Series/7. Parameters and Arguments.mp4 18.29 MB
2. Series/8. Create Series from Dataset with the pd.read_csv Method.mp4 60.36 MB
3. DataFrames I Introduction/1. Intro to DataFrames I Module.mp4 49.8 MB
3. DataFrames I Introduction/10. A Review of the .value_counts() Method.mp4 8.42 MB
3. DataFrames I Introduction/11. Drop Rows with Null Values.mp4 19.21 MB
3. DataFrames I Introduction/12. Fill in Null Values with the .fillna() Method.mp4 10.76 MB
3. DataFrames I Introduction/13. The .astype() Method.mp4 23.87 MB
3. DataFrames I Introduction/14. Sort a DataFrame with the .sort_values() Method, Part I.mp4 13.28 MB
3. DataFrames I Introduction/15. Sort a DataFrame with the .sort_values() Method, Part II.mp4 8.84 MB
3. DataFrames I Introduction/17. Sort DataFrame with the .sort_index() Method.mp4 6.57 MB
3. DataFrames I Introduction/18. Rank Values with the .rank() Method.mp4 13.17 MB
3. DataFrames I Introduction/2. Shared Methods and Attributes between Series and DataFrames.mp4 67.53 MB
3. DataFrames I Introduction/3. Differences between Shared Methods.mp4 13.1 MB
3. DataFrames I Introduction/4. Select One Column from a DataFrame.mp4 14.88 MB
3. DataFrames I Introduction/6. Select Two or More Columns from a DataFrame.mp4 9.94 MB
3. DataFrames I Introduction/8. Add New Column to DataFrame.mp4 17.24 MB
3. DataFrames I Introduction/9. Broadcasting Operations.mp4 18.23 MB
4. DataFrames II Filtering Data/1. This Module's Dataset + Memory Optimization.mp4 97.89 MB
4. DataFrames II Filtering Data/10. The .unique() and .nunique() Methods.mp4 8.2 MB
4. DataFrames II Filtering Data/2. Filter a DataFrame Based on A Condition.mp4 27.41 MB
4. DataFrames II Filtering Data/3. Filter with More than One Condition (AND - &).mp4 9.3 MB
4. DataFrames II Filtering Data/4. Filter with More than One Condition (OR - ).mp4 16.76 MB
4. DataFrames II Filtering Data/5. The .isin() Method.mp4 12.54 MB
4. DataFrames II Filtering Data/6. The .isnull() and .notnull() Methods.mp4 12.26 MB
4. DataFrames II Filtering Data/7. The .between() Method.mp4 16.77 MB
4. DataFrames II Filtering Data/8. The .duplicated() Method.mp4 19.57 MB
4. DataFrames II Filtering Data/9. The .drop_duplicates() Method.mp4 17.56 MB
5. DataFrames III Data Extraction/1. Intro to the DataFrames III Module + Import Dataset.mp4 23.37 MB
5. DataFrames III Data Extraction/10. Create Random Sample with the .sample() Method.mp4 9.34 MB
5. DataFrames III Data Extraction/11. Use the nsmallest nlargest methods to get rows with smallest largest values..mp4 12.08 MB
5. DataFrames III Data Extraction/12. Filtering the DataFrame with the where method.mp4 13.56 MB
5. DataFrames III Data Extraction/13. Filtering the DataFrame with the query method.mp4 19.93 MB
5. DataFrames III Data Extraction/14. A Review of the .apply() Method on Single Columns.mp4 11.75 MB
5. DataFrames III Data Extraction/15. The .apply() Method with Row Values.mp4 13.42 MB
5. DataFrames III Data Extraction/16. The .copy() Method.mp4 15.44 MB
5. DataFrames III Data Extraction/2. Use the set_index and reset_index methods to define a new DataFrame index.mp4 39.22 MB
5. DataFrames III Data Extraction/3. Retrieve Rows by Index Label with loc Accessor.mp4 61.13 MB
5. DataFrames III Data Extraction/4. Retrieve Rows by Index Position with iloc Accessor.mp4 39.56 MB
5. DataFrames III Data Extraction/5. Passing second arguments to the loc and iloc Accessors.mp4 45.86 MB
5. DataFrames III Data Extraction/6. Set New Value for a Specific Cell or Cells In a Row.mp4 19.94 MB
5. DataFrames III Data Extraction/7. Set Multiple Values in a DataFrame.mp4 38.57 MB
5. DataFrames III Data Extraction/8. Rename Index Labels or Columns in a DataFrame.mp4 58.07 MB
5. DataFrames III Data Extraction/9. Delete Rows or Columns from a DataFrame.mp4 16.22 MB
6. Working with Text Data/1. Intro to the Working with Text Data Section.mp4 32.3 MB
6. Working with Text Data/2. Common String Methods - lower, upper, title, and len.mp4 14.89 MB
6. Working with Text Data/3. Use the str.replace method to replace all occurrences of character with another.mp4 16 MB
6. Working with Text Data/4. Filtering a DataFrame's rows with string methods.mp4 15.55 MB
6. Working with Text Data/5. More String Methods - strip, lstrip, and rstrip for removing whitespace.mp4 9.55 MB
6. Working with Text Data/6. Invoking String Methods on Index and Columns.mp4 11.12 MB
6. Working with Text Data/7. Split Strings by Characters with the str.split Method.mp4 17.53 MB
6. Working with Text Data/8. More Practice with the str.split method on a Series.mp4 11.93 MB
6. Working with Text Data/9. Exploring the expand and n Parameters of the str.split Method.mp4 15.31 MB
7. MultiIndex/1. Intro to the MultiIndex Module.mp4 19.98 MB
7. MultiIndex/10. The .unstack() Method, Part 1.mp4 8.48 MB
7. MultiIndex/11. The .unstack() Method, Part 2.mp4 14.54 MB
7. MultiIndex/12. The .unstack() Method, Part 3.mp4 11.97 MB
7. MultiIndex/13. The pivot Method.mp4 12.12 MB
7. MultiIndex/14. Use the pivot_table method to create an aggregate summary of a DataFrame.mp4 22.17 MB
7. MultiIndex/15. Use the pd.melt method to create a narrow dataset from a wide one.mp4 17.26 MB
7. MultiIndex/2. Create a MultiIndex on a DataFrame with the set_index Method.mp4 45.7 MB
7. MultiIndex/3. Extract Index Level Values with the get_level_values Method.mp4 20.67 MB
7. MultiIndex/4. Change Index Level Name with the set_names Method.mp4 19.01 MB
7. MultiIndex/5. The sort_index Method on a MultiIndex DataFrame.mp4 35.24 MB
7. MultiIndex/6. Extract Rows from a MultiIndex DataFrame.mp4 47.01 MB
7. MultiIndex/7. The transpose Method on a MultiIndex DataFrame.mp4 35.64 MB
7. MultiIndex/8. The .swaplevel() Method.mp4 14.34 MB
7. MultiIndex/9. The .stack() Method.mp4 13.2 MB
8. The GroupBy Object/1. Intro to the Groupby Module.mp4 14.29 MB
8. The GroupBy Object/2. First Operations with groupby Object.mp4 23.09 MB
8. The GroupBy Object/3. Retrieve a group from a GroupBy object with the get_group Method.mp4 10.15 MB
8. The GroupBy Object/4. Methods on the Groupby Object and DataFrame Columns.mp4 20.5 MB
8. The GroupBy Object/5. Grouping by Multiple Columns.mp4 10.34 MB
8. The GroupBy Object/6. The .agg() Method.mp4 13.19 MB
8. The GroupBy Object/7. Iterating through Groups.mp4 21.38 MB
9. Merging, Joining, and Concatenating DataFrames/1. Intro to the Merging, Joining, and Concatenating Section.mp4 20.99 MB
9. Merging, Joining, and Concatenating DataFrames/10. The .join() Method.mp4 6.28 MB
9. Merging, Joining, and Concatenating DataFrames/11. The pd.merge() Method.mp4 6.84 MB
9. Merging, Joining, and Concatenating DataFrames/2. The pd.concat Method, Part 1.mp4 21.8 MB
9. Merging, Joining, and Concatenating DataFrames/3. The pd.concat Method, Part 2.mp4 30.59 MB
9. Merging, Joining, and Concatenating DataFrames/4. Inner Joins, Part 1.mp4 17.93 MB
9. Merging, Joining, and Concatenating DataFrames/5. Inner Joins, Part 2.mp4 17.76 MB
9. Merging, Joining, and Concatenating DataFrames/6. Outer Joins.mp4 25.94 MB
9. Merging, Joining, and Concatenating DataFrames/7. Left Joins.mp4 21 MB
9. Merging, Joining, and Concatenating DataFrames/8. The left_on and right_on Parameters.mp4 20.25 MB
9. Merging, Joining, and Concatenating DataFrames/9. Merging by Indexes with the left_index and right_index Parameters.mp4 22.71 MB
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