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| Section | Weight | Objectives |
|---|
| Topic 1: Python Programming for Data Analysis | 30% | - File Operations
- 1. Reading from files (text, CSV)
- 2. Writing to files
- 3. Context managers (with statement)
- Control Flow and Functions
- 1. Loops (for, while)
- 2. Conditional statements (if, elif, else)
- 3. Function definitions and parameters
- 4. Return values and scope
- Python Data Types and Structures
- 1. Numbers, strings, booleans
- 2. Lists, tuples, dictionaries, sets
- 3. Data type conversions
|
| Topic 2: Data Analysis Fundamentals | 20% | - Data Collection and Preparation
- 1. Data cleaning and preprocessing basics
- 2. Data sources and acquisition methods
- 3. Data import/export operations
- Introduction to Data Analysis
- 1. Data analysis process lifecycle
- 2. Types of data (structured, unstructured, semi-structured)
- 3. Data analysis concepts and terminology
|
| Topic 3: Working with Data Using Python Libraries | 30% | - Data Visualization
- 1. Seaborn introduction
- 2. Creating basic charts (line, bar, scatter, histogram)
- 3. Customizing plots
- 4. Matplotlib basics
- Pandas Library
- 1. Series and DataFrame structures
- 2. Handling missing data
- 3. Data selection and filtering
- 4. GroupBy operations
- 5. DataFrame operations (merge, join, concat)
- NumPy Fundamentals
- 1. Vectorized operations
- 2. NumPy arrays and operations
- 3. Array indexing and slicing
- 4. Basic statistical functions
|
| Topic 4: Applied Data Analysis Projects | 20% | - Exploratory Data Analysis (EDA)
- 1. Data distribution analysis
- 2. Correlation analysis
- 3. Pattern identification
- 4. Descriptive statistics computation
- Data Analysis Workflow
- 1. Problem definition
- 2. Results interpretation and presentation
- 3. Data exploration and cleaning
- 4. Analysis and modeling
|
>> PCAD-31-02 Exams <<
Latest PCAD-31-02 Exam Guide, PCAD-31-02 Actual Test Answers
The Python Institute PCAD-31-02 certification exam is one of the top-rated and valuable credentials in the Python Institute world. This Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) PCAD-31-02 exam questions is designed to validate the candidate's skills and knowledge. With Python Institute PCAD-31-02 exam dumps everyone can upgrade their expertise and knowledge level. By doing this the successful Python Institute PCAD-31-02 Exam candidates can gain several personal and professional benefits in their career and achieve their professional career objectives in a short time period.
Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q102-Q107):
NEW QUESTION # 102
Which method is typically used in Pandas to check if a column contains only values within an expected range?
- A. df.sample()
- B. df.sort_values()
- C. df.isin()
- D. df.clip()
Answer: C
NEW QUESTION # 103
Which of the following statistical measures are considered measures of central tendency?
(Choose two)
- A. Variance
- B. Mode
- C. Interquartile range
- D. Mean
Answer: B,D
NEW QUESTION # 104
Which type of chart is most appropriate when comparing the distribution of a numerical variable across multiple categories?
- A. Scatter plot
- B. Line chart
- C. Box plot
- D. Pie chart
Answer: C
NEW QUESTION # 105
What is the outcome of the following code?
data = [5, 10, 15]
result = [x**2 for x in data if x > 5]
print(result)
- A. [100, 225]
- B. [10, 15]
- C. [25, 100]
- D. [25, 100, 225]
Answer: A
NEW QUESTION # 106
Which of the following techniques are commonly used in the standardization of textual or categorical data during preprocessing?
(Choose two)
- A. Trimming whitespace from string values
- B. Applying logarithmic transformation to skewed data
- C. Scaling numeric features to a fixed range
- D. Replacing misspellings with a canonical category label
Answer: A,D
NEW QUESTION # 107
......
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