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| Section | Weight | Objectives |
|---|
| Working with Data and Performing Simple Analysis | 25% | - Data cleaning and preparation
- 1. Formatting and standardizing values
- 2. Filtering, sorting, transforming data
- 3. Handling missing values, duplicates, and errors
- Data acquisition and loading
- 1. Reading text, CSV, and structured files
- 2. Importing data from external sources
- Exploratory data analysis
- 1. Calculating mean, median, mode, range, variance, standard deviation
- 2. Identifying patterns, trends, and outliers
- Data aggregation and grouping
- 1. Summarizing and grouping datasets
|
| Data Visualization and Communication | 20% | - Creating basic visualizations
- 1. Line charts, bar charts, histograms, pie charts
- 2. Using text and simple plotting tools
- Principles of effective data visualization
- 1. Clarity, simplicity, and accuracy
- 2. Choosing appropriate chart types
- Interpreting and presenting results
- 1. Reporting findings clearly and concisely
- 2. Deriving conclusions and insights
|
| Introduction to Data and Data Analysis Concepts | 22.5% | - Data lifecycle and ethical considerations
- 1. Privacy, security, bias, and fairness in data
- 2. Data collection, storage, processing, usage, and sharing
- Basic statistical concepts
- 1. Population, sample, variable, observation
- 2. Descriptive vs inferential statistics
- Data types and measurement scales
- 1. Nominal, ordinal, interval, ratio scales
- 2. Qualitative vs quantitative data
- Definition and classification of data
- 1. Process of turning raw data into insights
- 2. Role of data in decision-making and business
- 3. Difference between data, information, and knowledge
|
| Python Basics for Data Analysis | 32.5% | - Core Python syntax and data types
- 1. Variables, numbers, strings, booleans
- 2. Lists, tuples, sets, dictionaries
- Built-in modules for data work
- 1. math, statistics, datetime, collections, csv
- Control flow and functions
- 1. Basic exception handling
- 2. Defining and calling functions, parameters, return values
- 3. Conditional statements, loops, iteration
- Introduction to NumPy
- 1. Arrays, basic operations, indexing, slicing
|
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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q37-Q42):
NEW QUESTION # 37
A program compares two values using == and is. The variables a = 256 and b = 256 are defined.
What is the expected result of a is b in most Python implementations?
- A. False
- B. True
- C. Error
- D. None
Answer: B
Explanation:
Python caches small integers for efficiency. Since 256 is typically within the cached range, both variables reference the same object in memory, making a is b evaluate to True.
NEW QUESTION # 38
You are developing a temperature control module for a laboratory incubator. Your objectives are to:
- generate timestamps every 10 minutes over a 3-hour span (i.e., 0 to 180 minutes), and
- simulate five evenly spaced target temperatures between 35.0°C and 37.0°C for system calibration.
Which code snippet correctly produces both sequences using NumPy? Select the best answer.
import numpy as np
- A. timestamps = np.linspace(0, 181, 10)
target_temps = np.arange(35.0, 37.0, 0.5)
import numpy a3 np - B. timestamps = np.linspace(0, 180, 10)
target_temps = np.arange(35.0, 37.0, 5)
import numpy as np - C. timestamps = np.arange(0, 180, 10)
target_temps = np.linspace(35.0, 37.0, 4)
import numpy as np - D. timestamps = np.arange(0, 181, 10)
target_temps = np.linspace(35.0, 37.0, 5)
Answer: D
Explanation:
np.arange(0, 181, 10) generates timestamps from 0 through 180 in 10-minute steps (end is excluded, so using 181 includes 180). np.linspace(35.0, 37.0, 5) generates five evenly spaced temperatures including both 35.0°C and 37.0°C.
NEW QUESTION # 39
A script defines a variable x = None and checks its truth value using a conditional statement. The developer wants to understand how Python evaluates None in Boolean contexts. What will bool(x) return?
- A. True
- B. False
- C. Error
- D. None
Answer: B
Explanation:
The value None represents the absence of a value and is treated as False in Boolean expressions. Therefore, calling bool(None) returns False, similar to empty containers or zero values.
NEW QUESTION # 40
A Python script evaluates the expression len(" "). The programmer assumes it might be zero because it looks empty. What will the actual result be?
Answer: C
Explanation:
A space is still a valid character in a string. Therefore, the string contains one character, and len("
") returns 1 instead of 0.
NEW QUESTION # 41
A script attempts to divide two numbers using / and //. The values are 7 and 2. The developer wants to understand the difference between true division and floor division. What are the results respectively?
- A. 3.5 and 3
- B. 3 and 3.5
- C. 3 and 4
- D. 4 and 3
Answer: A
Explanation:
The / operator performs true division, returning a float result of 3.5. The // operator performs floor division, truncating the decimal part and returning the integer value 3.
NEW QUESTION # 42
......
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