新版PCAD-31-02題庫 & PCAD-31-02信息資訊

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Python Institute PCAD-31-02 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Working with Data Using Python Libraries30%- Data Visualization
  • 1. Seaborn introduction
  • 2. Creating basic charts (line, bar, scatter, histogram)
  • 3. Customizing plots
  • 4. Matplotlib basics
- NumPy Fundamentals
  • 1. Array indexing and slicing
  • 2. Vectorized operations
  • 3. NumPy arrays and operations
  • 4. Basic statistical functions
- Pandas Library
  • 1. DataFrame operations (merge, join, concat)
  • 2. Data selection and filtering
  • 3. Series and DataFrame structures
  • 4. GroupBy operations
  • 5. Handling missing data
Topic 2: Applied Data Analysis Projects20%- Exploratory Data Analysis (EDA)
  • 1. Descriptive statistics computation
  • 2. Data distribution analysis
  • 3. Correlation analysis
  • 4. Pattern identification
- Data Analysis Workflow
  • 1. Analysis and modeling
  • 2. Data exploration and cleaning
  • 3. Results interpretation and presentation
  • 4. Problem definition
Topic 3: Python Programming for Data Analysis30%- Control Flow and Functions
  • 1. Return values and scope
  • 2. Conditional statements (if, elif, else)
  • 3. Loops (for, while)
  • 4. Function definitions and parameters
- File Operations
  • 1. Writing to files
  • 2. Reading from files (text, CSV)
  • 3. Context managers (with statement)
- Python Data Types and Structures
  • 1. Numbers, strings, booleans
  • 2. Data type conversions
  • 3. Lists, tuples, dictionaries, sets
Topic 4: Data Analysis Fundamentals20%- Data Collection and Preparation
  • 1. Data cleaning and preprocessing basics
  • 2. Data import/export operations
  • 3. Data sources and acquisition methods
- Introduction to Data Analysis
  • 1. Types of data (structured, unstructured, semi-structured)
  • 2. Data analysis concepts and terminology
  • 3. Data analysis process lifecycle

>> 新版PCAD-31-02題庫 <<

PCAD-31-02認證考古試題及參考答案

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最新的 Python Institute Certification PCAD-31-02 免費考試真題 (Q138-Q143):

問題 #138
When fetching DATETIME values from a SQL database into Python, which Python data type is most appropriate for storing and manipulating these values?

答案：C


問題 #139
Which term best describes the process of combining customer data from multiple systems into a single unified dataset?

答案：B


問題 #140
What is the outcome of the following code?
data = [5, 10, 15]
result = [x**2 for x in data if x > 5]
print(result)

答案：D


問題 #141
When creating a line chart with Matplotlib, which function is most appropriate to add a text label at a specific data point?

答案：D


問題 #142
Which practices help maintain data integrity across large datasets in Pandas workflows?
(Choose two)

答案：C,D


問題 #143
......

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PCAD-31-02信息資訊: https://www.newdumpspdf.com/PCAD-31-02-exam-new-dumps.html

P.S. NewDumps在Google Drive上分享了免費的、最新的PCAD-31-02考試題庫：https://drive.google.com/open?id=16Yja5dKa1mE8ZVkyQZZnEbr-A40dzU04