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Hướng dẫn soạn thảo bài giảng Elearning
Data Analysis with Pandas and Python
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Data Science Courses
pandas01
1. Installation and Setup
011 Windows - Unpack Course Materials The Startdown and Shutdown Process
011 Windows - Unpack Course Materials The Startdown and Shutdown Process
Sửa lần cuối: Thứ hai, 24 Tháng chín 2018, 10:37 AM
◄ 010 Windows - Access the Command Prompt and Update Anaconda Libraries
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1. Introduction to the Course
2. Mac OS - Download the Anaconda Distribution
3. Mac OS - Install Anaconda Distribution
005 Mac OS - Access the Terminal.mp4
006 Mac OS - Update Anaconda Libraries
007 Mac OS - Unpack Course Materials The Startdown and Shutdown Process
008 Windows - Download the Anaconda Distribution
009 Windows - Install Anaconda Distribution
010 Windows - Access the Command Prompt and Update Anaconda Libraries
012 Intro to the Jupyter Notebook Interface
013 Cell Types and Cell Modes
014 Code Cell Execution
015 Popular Keyboard Shortcuts
016 Import Libraries into Jupyter Notebook
017 Python Crash Course Part 1 - Data Types and Variables
018 Python Crash Course Part 2 - Lists
019 Python Crash Course Part 3 - Dictionaries
01 Installation and Setup/020 Python Crash Course Part 4 - Operators
021 Python Crash Course Part 5 - Functions
Diễn đàn tin tức
022 Create Jupyter Notebook for the Series Module
023 Create A Series Object from a Python List
024 Create A Series Object from a Python Dictionary
025 Intro to Attributes
026 Intro to Methods
027 Parameters and Arguments
028 Import Series with the .read_csv() Method
029 The .head() and .tail() Methods.
030 Python Built-In Functions
031 More Series Attributes
032 The .sort_values() Method
033 The inplace Paramete
034 The .sort_index() Method
035 Pythons in Keyword
036 Extract Series Values by Index Position
037 Extract Series Values by Index Label
038 The .get() Method on a Series
039 Math Methods on Series Objects
040 The .idxmax() and .idxmin() Methods
041 The .value_counts() Method
042 The .apply() Method
043 The .map() Method
044 Intro to DataFrames I Module
045 Shared Methods and Attributes between Series and DataFrames
046 Differences between Shared Methods
047 Select One Column from a DataFrame
048 Select Two or More Columns from a DataFrame
049 Add New Column to DataFrame
050 Broadcasting Operations
051 A Review of the .value_counts() Method
052 Drop Rows with Null Values
053 Fill in Null Values with the .fillna() Method
054 The .astype() Method
055 Sort a DataFrame with the .sort_values() Method Part I
056 Sort a DataFrame with the .sort_values() Method Part II
057 Sort DataFrame with the .sort_index() Method
058 Rank Values with the .rank() Method
059 This Modules Dataset Memory Optimization
060 Filter a DataFrame Based on A Condition
061 Filter with More than One Condition (AND - )
062 Filter with More than One Condition (OR - )
064 The .isnull() and .notnull() Methods
065 The .between() Method
066 The .duplicated() Method
067 The .drop_duplicates() Method
68 The .unique() and .nunique() Methods
069 Intro to the DataFrames III Module Import Dataset
070 The .set_index() and .reset_index() Methods
071 Retrieve Rows by Index Label with .loc
072 Retrieve Rows by Index Position with .iloc
073 The Catch-All .ix Method
074 Second Arguments to .loc .iloc and .ix Methods
075 Set New Values for a Specific Cell or Row
076 Set Multiple Values in DataFrame
077 Rename Index Labels or Columns in a DataFrame
078 Delete Rows or Columns from a DataFrame
079 Create Random Sample with the .sample() Method
080 The .nsmallest() and .nlargest() Methods
081 Filtering with the .where() Method
082 The .query() Method
083 A Review of the .apply() Method on Single Columns
084 The .apply() Method with Row Values
085 The .copy() Method
086 Intro to the Working with Text Data Module
087 Common String Methods - lower upper title and len
088 The .str.replace() Method
089 Filtering with String Methods
090 More String Methods - strip lstrip and rstrip
091 String Methods on Index and Columns.
092 Split Strings by Characters with .str.split() Method
093 More Practice with Splits
094 The expand and n Parameters of the .str.split() Method
095 Intro to the MultiIndex Module
096 Create a MultiIndex with the set_index() Method.
097 The .get_level_values() Method.
098 The .set_names() Method.
099 The sort_index() Method.
100 Extract Rows from a MultiIndex DataFrame
101 The .transpose() Method and MultiIndex on Column Level
102 The .swaplevel() Method.
103 The .stack() Method
104 The .unstack() Method Part 1
105 The .unstack() Method Part 2
106 The .unstack() Method Part 3
107 The .pivot() Method
108 The .pivot_table() Method
109 The pd.melt() Method
110 Intro to the Groupby Module
111 First Operations with groupby Object
112 Retrieve A Group with the .get_group() Method
113 Methods on the Groupby Object and DataFrame Columns
114 Grouping by Multiple Columns
115 The .agg() Method
116 Iterating through Groups.
117 Intro to the Merging Joining and Concatenating Module
118 The pd.concat() Method Part 1
119 The pd.concat() Method Part 2
120 The .append() Method on a DataFrame
121 Inner Joins Part 1
122 Inner Joins Part 2
123 Outer Joins.
124 Left Joins
125 The left_on and right_on Parameters
126 Merging by Indexes with the left_index and right_index Parameters
127 The .join() Method
128 The pd.merge() Method
129 Intro to the Working with Dates and Times Module
130 Review of Pythons datetime Module
131 The pandas Timestamp Object
132 The pandas DateTimeIndex Object
133 The pd.to_datetime() Method
134 Create Range of Dates with the pd.date_range() Method Part 1
135 Create Range of Dates with the pd.date_range() Method Part 2
136 Create Range of Dates with the pd.date_range() Method Part 3
137 The .dt Accessor
138 Install pandas-datareader Library
139 Import Financial Data Set with pandas_datareader Library
140 Selecting Rows from a DataFrame with a DateTimeIndex
141 Timestamp Object Attributes
142 The .truncate() Method
143 pd.DateOffset Objects
144 More Fun with pd.DateOffset Objects
145 The pandas Timedelta Object
146 Timedeltas in a Dataset
152 Convert Panel to a MultiIndex DataFrame (and Vice Versa)
153 The .major_xs() Method
147 Intro to the Module Fetch Panel Dataset from Google Finance
148 The Axes of a Panel Object
149 Panel Attributes
150 Use Bracket Notation to Extract a DataFrame from a Panel
151 Extracting with the .loc .iloc and .ix Methods
152 Convert Panel to a MultiIndex DataFrame (and Vice Versa)
153 The .major_xs() Method.
154 The .minor_xs() Method.
155 Transpose a Panel with the .transpose() Method
156 The .swapaxes() Method
157 Intro to the Input and Output Module
158 Feed pd.read_csv() Method a URL Argument
159 Quick Object Conversions
160 Export DataFrame to CSV File with the .to_csv() Method
161 Install xlrd and openpyxl Libraries to Read and Write Excel Files
162 Import Excel File into pandas
163 Export Excel File
164 Intro to Visualization Module
165 The .plot() Method
166 Modifying Aesthetics with Templates
167 Bar Graphs
168 Pie Charts
169 Histograms
170 Introduction to the Options and Settings Module
171 Changing pandas Options with Attributes and Dot Syntax
172 Changing pandas Options with Methods
173 The precision Option
174 Conclusion
012 Intro to the Jupyter Notebook Interface ►
pandas01
1. Installation and Setup
2. Series
03 DataFrames I
04 DataFrames II
05 DataFrames III
06 Working with Text Data/
07 MultiIndex
08 GroupBy
09 Merging Joining and Concatenating
10 Working with Dates and Times
11 Panels
12 Input and Output
13 Visualization
14 Options and Settings
15 Conclusion
Topic 15
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