Python for Data Analytics
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Course Content
Buổi 1: GETTING STARTED
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1. Introduction
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2. Python for Dev vs Python for DA
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3. Course structure
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4. Learning method
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5. Data Analysis Workflow with Python
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6. Set up Google Colab
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7. Quotes and Comments
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8. Line & identification
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9. Python variable
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10. Input data
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11. Print()
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Quiz buổi 1
Buổi 2: OPERATORS & DATA TYPES
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1. Today’s plan
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2. Operator #1
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3. Operator #1 Challenge
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4. Operator #1 Solution
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5. Operator #2
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6. Numeric & Boolean
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7. String
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8. String Challenge
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9. String Solution
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10. List
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11. List Challenge
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12. List Solution
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13. Tupple
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14. Dictionary
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15. Dictionary Challenge
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16. Dictionary Solution
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Quiz buổi 2
Buổi 3: PRACTICE
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Practice 1
Buổi 4: LOGICAL CONDITION
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1. Today’s plan
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2. If-else
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3. If-else Challenge
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4. If-else Solution
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5. Loop
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6. Loop Challenge
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7. Loop Solution
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8. Nested Loop
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9. Nested Loop Challenge
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10. Nested Loop Solution
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11. Break & Continue
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12. Break & Continue Challenge
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13. Break & Continue Solution
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14. List Comprehension
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15. List Comprehension Challenge
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16. List Comprehension Solution
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Quiz 4
Buổi 5: [PHASE 1] PRACTICE
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PRACTICE 2
Buổi 6: FUNCTION
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1. Today’s plan
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2. What is a Function?
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3. UDF
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4. UDF Challenge – Solution
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5. Lambda
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6. Built-in function & Lambda
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7. Built-in function & Lambda challenge
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8. Built-in function & Lambda Solution
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9. Package, Libary (from import/ import)
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Quiz buổi 6
Buổi 7: PRACICE
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PRACTICE 3
Buổi 8: SERIES & GATHERING DATA
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1. Data Description
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2. Today’s plan
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3. Pandas introduction
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4. Create Series
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5. Series Selection
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6. Series Operators
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7. Series với numpy
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8. Series Challenge
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9. Series Solution
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10. Gathering data process
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11. Create Dataframe
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12. Quick Explore Dataframe
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13. Gathering data Challenge
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14. Gathering data Solution
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Quiz buổi 8
Buổi 9: DATA SELECTION & GROUPING
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1. Today’s plan
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2. Select data
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3. Drop_duplicates()
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4. Filtering
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5. Filtering Challenge
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6. Filtering Solution
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7. Sorting
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8. Mathetics operator
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9. Mathetics operator Challenge
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10. Mathetics operator Solution
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11. Aggregate Function
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12. Grouping #1
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13. Grouping Challenge
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14. Grouping Solution
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Quiz buổi 9
Buổi 10: PRACTICE
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PRACTICE 4
Buổi 11: LOGIC CONDITION & CREATE SINGLE TABLE
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1. Today’s plan
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2. Group by – Transform
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3. Groupby-Trasform() Challenge
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4. Groupby-Trasform() Solution
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5. Condition
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6. Condition Challenge
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7. Condition Solution
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8. Concat
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9. Type of Joins
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10. Join demo
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11. Join Challenge
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12. Join Solution
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Quiz buổi 11
Buổi 12: WORKING WITH STRING & DATETIME DATA
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1. Today’s plan
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2. upper(), lower(), capitaize(), len()
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3. Find Pattern
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4. Find Pattern Challenge
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5. Find pattern solution
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6. Extract
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7. replace()
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8. split(), Concatenation
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9. split() challenge
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10. split() solution
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11. pd.to_datetime()
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12. Extract datetime component
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13. Datetime Calculation
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14. shift() Method
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15. rolling() Method
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Quiz buổi 12
Buổi 13: PRACTICE
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PRACTICE 5
Buổi 14: CLEAN DATA
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1. Clean data Overview
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2. Issue 1: Datatypes
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3. Issue 1: Datatypes Challenge
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4. Issue 1: Datatypes Solution
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5. Issue 2: Inconsistent Text & Types
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6. Issue 2: Inconsistent Text & Types Challenge
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7. Issue 2: Inconsistent Text & Types Solution
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8. Issue 3: Duplicates
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9. Issue 4: Missing data
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10. Issue 4: Missing data Challenge
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11. Issue 4: Missing data Solution
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Quiz buổi 14
Buổi 15: [PHASE 2] PRACTICE
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PRACTICE 6
Buổi 16: MID COURSE TEST
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MID COURSE TEST
Buổi 17: VISUALIZATION #1
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1. Today’s plan
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2. Why Statistics ?
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3. Data types in Statistics
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5. Measure of central tendency
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6. Measure of Variability
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7. Measure of Correlation
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8. How to choose the right chart #1
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9. How to choose the right chart #2
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Quiz buổi 17
Buổi 18: [PHASE 3] VISUALIZATION #2
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1. Today’s plan
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2. Distribution Plots #1
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3. Distribution Plots #2
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4. Relationship Plots
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5. Ranking Plots
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6. Subplot
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Buổi 19: PRACTICE
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PRACTICE 7
Buổi 20: PROBLEM SOLVING STRATEGY
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1. Project component
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2. Problem solving framework
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3. Understand & Clarify problem
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4. Structure problem
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5. Ask the right question
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6. Load & Clean Data #1
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7. Load & Clean Data #2
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Buổi 21: PRACTICE
Buổi 22: DATA ANALYSIS #1
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1. How to Aquire New Customer – Current Situation
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2. How to Aquire New Customer – Top High-Performing Customer Regions
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3. How to Aquire New Customer – Top-selling Products
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4. How to Aquire New Customer – Top High-Performing Merchants
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5. Retaining Existing Customers – Cohort Analysis
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Buổi 23: DATA ANALYSIS # 2
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1. How to Improve Customer Experience – Lead Time Performance #1
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2. How to Improve Customer Experience – Lead Time Performance #2
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3. How to Improve Customer Experience – Enhance Dispatch Time
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4. How to Improve Customer Experience – Enhance Delivery Time
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5. How to Improve Customer Experience- Enhance Payment Processing
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Buổi 24: DATA ANALYSIS #3
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1. How to Increase Order Frequency – Trend Over Time Analysis
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2. How to Increase Order Frequency – Customer Segmentation Analysis
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3. How to Increase the # of Items per Order
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4. Fix duplicates issue
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Buổi 25 – 28: PRACTICE
Buổi 29: PRESENTATION & STORY TELLING
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1. PRESENTATION & STORY TELLING #1
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2. PRESENTATION & STORY TELLING #2
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