Quick check · Syntax
Level I · Optional · Open anytime
Introductory Python for Research
Start by reading a few lines at a time. Learn what Python objects represent, how a program makes decisions, and how pandas organizes a small research table. Predict each result before revealing it; no installation is needed to use these checks.
Study any section in any order. These checks do not affect your core course or assessments. Choice answers and elective progress are tracked in this browser.
Try six coding tasks with separate solutions
Read the code, predict the result, then check your reasoning. Each example has revealable output. To run or edit the snippets, use your own Python environment.
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Section 1 of 2
Read syntax, names, and basic arithmetic
Python executes statements in order. The assignment price = 100 binds the name price to an object representing 100. Names are case-sensitive: Price and price are different. Comments begin with # and describe intent without changing the result.
Integers such as 100 have type int; decimal values such as 0.05 usually have type float. Text uses quotes and has type str. The operators +, − (written as - in code), *, /, and ** mean addition, subtraction, multiplication, division, and exponentiation. Parentheses clarify evaluation order. Use = to assign and == to compare values.
print displays a value. An f-string starts with f before its opening quote and inserts expressions inside braces. The format :.2f displays two decimal places. Formatting changes the displayed text, not the underlying calculation; binary floating-point values can contain tiny representation differences.
wealth = 100
return_rate = 0.05 # 5%, expressed as a fraction
ending_wealth = wealth * (1 + return_rate)
print(f"{ending_wealth:.2f}")Reveal the expected output
105.00
Keep in mind: Read each statement as a small operation on named values.
Pause and try two quick checks.
You can move on at any time. Each answer explains the reasoning.
Quick check · Types
What does the expression "12" + "3" produce?
Further reading and documentation
- Python tutorial: numbers, text, and lists ↗
- Python tutorial: data structures ↗
- Python tutorial: control flow and functions ↗
- Python reference: objects and mutability ↗
- pandas: introductory overview ↗
- pandas: selecting rows and columns ↗
- pandas: missing data ↗
- pandas: fractional change ↗
- pandas: grouping and summary statistics ↗
- pandas: merging tables ↗
- pandas: Copy-on-Write and assignment ↗
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The full elective is included with Level I enrollment, together with the core course and the official examination.
Go further · Optional resources
Build your mathematics, statistics, and Python toolkit.
Open these resources at any time. They are separate from the core modules and do not count toward examination eligibility, practice scores, or certification. Programming remains optional.
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Mathematical Foundations & Linear Algebra
Build mathematical confidence, then study pure linear algebra with step-by-step examples, geometric interpretation, and quick checks, closing with mental math techniques.
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Introduction to Descriptive Statistics
A compact companion to the core course: calculate medians and modes, compare ranges and quartiles, read empirical percentiles, and build honest frequency summaries.
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Introductory Python for Research
Learn to read basic Python and follow simple pandas workflows, with code examples and instant-feedback checks.
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