/Python & Data Analytics/Phase 1

Phase 1Days 1-12

Python & Exploratory Analysis Foundations

Ask a data question on Day 1 while learning the Python needed to answer it

Phase Goal

Run a reproducible Python analysis, inspect a small dataset, and distinguish a useful pattern from a quality problem.

Progress

Notes

Open the written lectures for this course before checking off the phase topics.

Projects

Neighbourhood Cooling-Centre Access Brief

Day 1: The Analyst Loop & First Dataset

Build the first-principles mental model for Question → rows → checks → evidence → decision; name the question it answers and the unit of analysisPredict and trace a tiny example of Question → rows → checks → evidence → decision before inspecting the resultApply Question → rows → checks → evidence → decision to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Question → rows → checks → evidence → decision; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Python, VS Code, Jupyter cells, and restart-run-all discipline; name the question it answers and the unit of analysisPredict and trace a tiny example of Python, VS Code, Jupyter cells, and restart-run-all discipline before inspecting the resultApply Python, VS Code, Jupyter cells, and restart-run-all discipline to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Python, VS Code, Jupyter cells, and restart-run-all discipline; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for CSV rows, columns, headers, types, and analytical grain; name the question it answers and the unit of analysisPredict and trace a tiny example of CSV rows, columns, headers, types, and analytical grain before inspecting the resultApply CSV rows, columns, headers, types, and analytical grain to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind CSV rows, columns, headers, types, and analytical grain; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for First EDA with shape, columns, head, value counts, and missingness; name the question it answers and the unit of analysisPredict and trace a tiny example of First EDA with shape, columns, head, value counts, and missingness before inspecting the resultApply First EDA with shape, columns, head, value counts, and missingness to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind First EDA with shape, columns, head, value counts, and missingness; diagnose the visible failure and perform the corrective check

Retrieve one recent mechanism and one older prerequisite before consulting notesComplete a guided example, then reconstruct its critical path from a blank artifactSolve a changed task that requires choosing among already-taught toolsRecord the decision changed, failure tested, help used, and adaptive 1/3/7/14/30-day review cue

Day 2: Values, Variables & Business Arithmetic

Build the first-principles mental model for Names, assignment, literals, and snake_case; name the question it answers and the unit of analysisPredict and trace a tiny example of Names, assignment, literals, and snake_case before inspecting the resultApply Names, assignment, literals, and snake_case to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Names, assignment, literals, and snake_case; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Integers, floats, precedence, ratios, rates, and percentages; name the question it answers and the unit of analysisPredict and trace a tiny example of Integers, floats, precedence, ratios, rates, and percentages before inspecting the resultApply Integers, floats, precedence, ratios, rates, and percentages to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Integers, floats, precedence, ratios, rates, and percentages; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Strings, f-strings, labels, and units; name the question it answers and the unit of analysisPredict and trace a tiny example of Strings, f-strings, labels, and units before inspecting the resultApply Strings, f-strings, labels, and units to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Strings, f-strings, labels, and units; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Types, conversion failures, and misleading precision; name the question it answers and the unit of analysisPredict and trace a tiny example of Types, conversion failures, and misleading precision before inspecting the resultApply Types, conversion failures, and misleading precision to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Types, conversion failures, and misleading precision; diagnose the visible failure and perform the corrective check

Day 3: Conditions & Data Rules

Build the first-principles mental model for Booleans, comparisons, membership, and boundaries; name the question it answers and the unit of analysisPredict and trace a tiny example of Booleans, comparisons, membership, and boundaries before inspecting the resultApply Booleans, comparisons, membership, and boundaries to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Booleans, comparisons, membership, and boundaries; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for if/elif/else as ordered business rules; name the question it answers and the unit of analysisPredict and trace a tiny example of if/elif/else as ordered business rules before inspecting the resultApply if/elif/else as ordered business rules to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind if/elif/else as ordered business rules; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for and/or/not precedence and truth tables; name the question it answers and the unit of analysisPredict and trace a tiny example of and/or/not precedence and truth tables before inspecting the resultApply and/or/not precedence and truth tables to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind and/or/not precedence and truth tables; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Missing categories and rule-order bugs; name the question it answers and the unit of analysisPredict and trace a tiny example of Missing categories and rule-order bugs before inspecting the resultApply Missing categories and rule-order bugs to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Missing categories and rule-order bugs; diagnose the visible failure and perform the corrective check

Day 4: Lists & Row-Level Thinking

Build the first-principles mental model for Lists, indexing, slicing, mutation, and copying; name the question it answers and the unit of analysisPredict and trace a tiny example of Lists, indexing, slicing, mutation, and copying before inspecting the resultApply Lists, indexing, slicing, mutation, and copying to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Lists, indexing, slicing, mutation, and copying; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Iteration over observations with for loops; name the question it answers and the unit of analysisPredict and trace a tiny example of Iteration over observations with for loops before inspecting the resultApply Iteration over observations with for loops to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Iteration over observations with for loops; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for range, enumerate, accumulators, and running checks; name the question it answers and the unit of analysisPredict and trace a tiny example of range, enumerate, accumulators, and running checks before inspecting the resultApply range, enumerate, accumulators, and running checks to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind range, enumerate, accumulators, and running checks; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Comprehensions versus explicit loops for readable transformations; name the question it answers and the unit of analysisPredict and trace a tiny example of Comprehensions versus explicit loops for readable transformations before inspecting the resultApply Comprehensions versus explicit loops for readable transformations to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Comprehensions versus explicit loops for readable transformations; diagnose the visible failure and perform the corrective check

Day 5: Dictionaries & Records

Build the first-principles mental model for Key-value records and safe lookup; name the question it answers and the unit of analysisPredict and trace a tiny example of Key-value records and safe lookup before inspecting the resultApply Key-value records and safe lookup to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Key-value records and safe lookup; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Nested records as table-shaped data; name the question it answers and the unit of analysisPredict and trace a tiny example of Nested records as table-shaped data before inspecting the resultApply Nested records as table-shaped data to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Nested records as table-shaped data; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Counting categories and grouping by key; name the question it answers and the unit of analysisPredict and trace a tiny example of Counting categories and grouping by key before inspecting the resultApply Counting categories and grouping by key to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Counting categories and grouping by key; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Missing keys, duplicate identifiers, and schema drift; name the question it answers and the unit of analysisPredict and trace a tiny example of Missing keys, duplicate identifiers, and schema drift before inspecting the resultApply Missing keys, duplicate identifiers, and schema drift to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Missing keys, duplicate identifiers, and schema drift; diagnose the visible failure and perform the corrective check

Day 6: Strings for Messy Categories

Build the first-principles mental model for String indexing, slicing, immutability, and Unicode; name the question it answers and the unit of analysisPredict and trace a tiny example of String indexing, slicing, immutability, and Unicode before inspecting the resultApply String indexing, slicing, immutability, and Unicode to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind String indexing, slicing, immutability, and Unicode; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for strip, case normalization, replace, split, and join; name the question it answers and the unit of analysisPredict and trace a tiny example of strip, case normalization, replace, split, and join before inspecting the resultApply strip, case normalization, replace, split, and join to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind strip, case normalization, replace, split, and join; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Validation with membership and character tests; name the question it answers and the unit of analysisPredict and trace a tiny example of Validation with membership and character tests before inspecting the resultApply Validation with membership and character tests to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Validation with membership and character tests; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Over-cleaning and preserving raw text; name the question it answers and the unit of analysisPredict and trace a tiny example of Over-cleaning and preserving raw text before inspecting the resultApply Over-cleaning and preserving raw text to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Over-cleaning and preserving raw text; diagnose the visible failure and perform the corrective check

Day 7: Loops That Aggregate

Build the first-principles mental model for Accumulator patterns for totals, counts, minima, and maxima; name the question it answers and the unit of analysisPredict and trace a tiny example of Accumulator patterns for totals, counts, minima, and maxima before inspecting the resultApply Accumulator patterns for totals, counts, minima, and maxima to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Accumulator patterns for totals, counts, minima, and maxima; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Nested loops and relationship-aware iteration; name the question it answers and the unit of analysisPredict and trace a tiny example of Nested loops and relationship-aware iteration before inspecting the resultApply Nested loops and relationship-aware iteration to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Nested loops and relationship-aware iteration; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for break, continue, loop else, and control-flow traces; name the question it answers and the unit of analysisPredict and trace a tiny example of break, continue, loop else, and control-flow traces before inspecting the resultApply break, continue, loop else, and control-flow traces to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind break, continue, loop else, and control-flow traces; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Off-by-one, double-counting, and denominator failures; name the question it answers and the unit of analysisPredict and trace a tiny example of Off-by-one, double-counting, and denominator failures before inspecting the resultApply Off-by-one, double-counting, and denominator failures to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Off-by-one, double-counting, and denominator failures; diagnose the visible failure and perform the corrective check

Day 8: Functions for Repeatable Analysis

Build the first-principles mental model for Parameters, arguments, returns, and pure transformations; name the question it answers and the unit of analysisPredict and trace a tiny example of Parameters, arguments, returns, and pure transformations before inspecting the resultApply Parameters, arguments, returns, and pure transformations to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Parameters, arguments, returns, and pure transformations; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Default and keyword arguments without hidden state; name the question it answers and the unit of analysisPredict and trace a tiny example of Default and keyword arguments without hidden state before inspecting the resultApply Default and keyword arguments without hidden state to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Default and keyword arguments without hidden state; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Docstrings, type hints, and single-purpose design; name the question it answers and the unit of analysisPredict and trace a tiny example of Docstrings, type hints, and single-purpose design before inspecting the resultApply Docstrings, type hints, and single-purpose design to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Docstrings, type hints, and single-purpose design; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Scope, mutation, None returns, and testable boundaries; name the question it answers and the unit of analysisPredict and trace a tiny example of Scope, mutation, None returns, and testable boundaries before inspecting the resultApply Scope, mutation, None returns, and testable boundaries to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Scope, mutation, None returns, and testable boundaries; diagnose the visible failure and perform the corrective check

Day 9: Reading CSV Data Safely

Build the first-principles mental model for Paths, working directories, and pathlib; name the question it answers and the unit of analysisPredict and trace a tiny example of Paths, working directories, and pathlib before inspecting the resultApply Paths, working directories, and pathlib to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Paths, working directories, and pathlib; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for with blocks, encoding, newline handling, and csv.DictReader; name the question it answers and the unit of analysisPredict and trace a tiny example of with blocks, encoding, newline handling, and csv.DictReader before inspecting the resultApply with blocks, encoding, newline handling, and csv.DictReader to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind with blocks, encoding, newline handling, and csv.DictReader; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Schema checks, row counts, and source metadata; name the question it answers and the unit of analysisPredict and trace a tiny example of Schema checks, row counts, and source metadata before inspecting the resultApply Schema checks, row counts, and source metadata to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Schema checks, row counts, and source metadata; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Malformed rows, delimiters, and immutable raw inputs; name the question it answers and the unit of analysisPredict and trace a tiny example of Malformed rows, delimiters, and immutable raw inputs before inspecting the resultApply Malformed rows, delimiters, and immutable raw inputs to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Malformed rows, delimiters, and immutable raw inputs; diagnose the visible failure and perform the corrective check

Day 10: Summaries Before Charts

Build the first-principles mental model for Count, sum, min, max, mean, and median; name the question it answers and the unit of analysisPredict and trace a tiny example of Count, sum, min, max, mean, and median before inspecting the resultApply Count, sum, min, max, mean, and median to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Count, sum, min, max, mean, and median; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Frequency tables, proportions, and denominator labels; name the question it answers and the unit of analysisPredict and trace a tiny example of Frequency tables, proportions, and denominator labels before inspecting the resultApply Frequency tables, proportions, and denominator labels to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Frequency tables, proportions, and denominator labels; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Sorting, top-N, ties, and the long tail; name the question it answers and the unit of analysisPredict and trace a tiny example of Sorting, top-N, ties, and the long tail before inspecting the resultApply Sorting, top-N, ties, and the long tail to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Sorting, top-N, ties, and the long tail; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Small samples, missing values, and hidden variation; name the question it answers and the unit of analysisPredict and trace a tiny example of Small samples, missing values, and hidden variation before inspecting the resultApply Small samples, missing values, and hidden variation to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Small samples, missing values, and hidden variation; diagnose the visible failure and perform the corrective check

Day 11: First Evidence Chart

Build the first-principles mental model for Question-first chart selection; name the question it answers and the unit of analysisPredict and trace a tiny example of Question-first chart selection before inspecting the resultApply Question-first chart selection to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Question-first chart selection; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Matplotlib figure, axes, marks, labels, and scales; name the question it answers and the unit of analysisPredict and trace a tiny example of Matplotlib figure, axes, marks, labels, and scales before inspecting the resultApply Matplotlib figure, axes, marks, labels, and scales to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Matplotlib figure, axes, marks, labels, and scales; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Bar charts and histograms from checked summaries; name the question it answers and the unit of analysisPredict and trace a tiny example of Bar charts and histograms from checked summaries before inspecting the resultApply Bar charts and histograms from checked summaries to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Bar charts and histograms from checked summaries; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Truncated axes, crowded labels, and distorted evidence; name the question it answers and the unit of analysisPredict and trace a tiny example of Truncated axes, crowded labels, and distorted evidence before inspecting the resultApply Truncated axes, crowded labels, and distorted evidence to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Truncated axes, crowded labels, and distorted evidence; diagnose the visible failure and perform the corrective check

Day 12: Phase Project — Heat Access Brief

Build the first-principles mental model for Scope, user, decision, grain, and data dictionary; name the question it answers and the unit of analysisPredict and trace a tiny example of Scope, user, decision, grain, and data dictionary before inspecting the resultApply Scope, user, decision, grain, and data dictionary to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Scope, user, decision, grain, and data dictionary; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Python cleaning and summary workflow with assertions; name the question it answers and the unit of analysisPredict and trace a tiny example of Python cleaning and summary workflow with assertions before inspecting the resultApply Python cleaning and summary workflow with assertions to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Python cleaning and summary workflow with assertions; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for One table and two charts for distinct questions; name the question it answers and the unit of analysisPredict and trace a tiny example of One table and two charts for distinct questions before inspecting the resultApply One table and two charts for distinct questions to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind One table and two charts for distinct questions; diagnose the visible failure and perform the corrective check

Build the first-principles mental model for Recommendation, uncertainty, limitations, and reproducible README; name the question it answers and the unit of analysisPredict and trace a tiny example of Recommendation, uncertainty, limitations, and reproducible README before inspecting the resultApply Recommendation, uncertainty, limitations, and reproducible README to a realistic analyst decision while stating assumptions, units, and boundariesBreak one assumption behind Recommendation, uncertainty, limitations, and reproducible README; diagnose the visible failure and perform the corrective check

Deliver Neighbourhood Cooling-Centre Access Brief for a city resilience coordinator; support the decision: which neighbourhoods need extended cooling-centre hours during the next heat alert?Reconstruct the critical workflow without the example open and disclose help usedFind and repair a planted data, logic, or communication failure with evidenceRespond to a changed requirement without being told which technique to useState limitations, non-goals, uncertainty, and what evidence would change the recommendation

Capstone

Neighbourhood Cooling-Centre Access Brief

Build for a city resilience coordinator. The result must support this decision: which neighbourhoods need extended cooling-centre hours during the next heat alert? Include reproducible inputs, validation evidence, one tested failure, a changed requirement, and an explicit non-goal.

Reproducible source-to-output workflow
Documented quality checks and assumptions
Decision-ready output for a named user
Independent reconstruction and transfer evidence

Phase Complete!

After this phase, you'll be able to:

The Analyst Loop & First Dataset
Values, Variables & Business Arithmetic
Conditions & Data Rules
Lists & Row-Level Thinking
Dictionaries & Records
Strings for Messy Categories
Loops That Aggregate
Functions for Repeatable Analysis

Independently deliver Neighbourhood Cooling-Centre Access Brief, diagnose a planted failure, explain the decision logic, and transfer the workflow to a changed requirement.

Back to all phases

Phase Goal

Day 1: The Analyst Loop & First Dataset

Question → rows → checks → evidence → decision

Python, VS Code, Jupyter cells, and restart-run-all discipline

CSV rows, columns, headers, types, and analytical grain

First EDA with shape, columns, head, value counts, and missingness

Practice, retrieval, and analyst judgment

Day 2: Values, Variables & Business Arithmetic

Names, assignment, literals, and snake_case

Integers, floats, precedence, ratios, rates, and percentages

Strings, f-strings, labels, and units

Types, conversion failures, and misleading precision

Practice, retrieval, and analyst judgment

Day 3: Conditions & Data Rules

Booleans, comparisons, membership, and boundaries

if/elif/else as ordered business rules

and/or/not precedence and truth tables

Missing categories and rule-order bugs

Practice, retrieval, and analyst judgment

Day 4: Lists & Row-Level Thinking

Lists, indexing, slicing, mutation, and copying

Iteration over observations with for loops

range, enumerate, accumulators, and running checks

Comprehensions versus explicit loops for readable transformations

Practice, retrieval, and analyst judgment

Day 5: Dictionaries & Records

Key-value records and safe lookup

Nested records as table-shaped data

Counting categories and grouping by key

Missing keys, duplicate identifiers, and schema drift

Practice, retrieval, and analyst judgment

Day 6: Strings for Messy Categories

String indexing, slicing, immutability, and Unicode

strip, case normalization, replace, split, and join

Validation with membership and character tests

Over-cleaning and preserving raw text

Practice, retrieval, and analyst judgment

Day 7: Loops That Aggregate

Accumulator patterns for totals, counts, minima, and maxima

Nested loops and relationship-aware iteration

break, continue, loop else, and control-flow traces

Off-by-one, double-counting, and denominator failures

Practice, retrieval, and analyst judgment

Day 8: Functions for Repeatable Analysis

Parameters, arguments, returns, and pure transformations

Default and keyword arguments without hidden state

Docstrings, type hints, and single-purpose design

Scope, mutation, None returns, and testable boundaries

Practice, retrieval, and analyst judgment

Day 9: Reading CSV Data Safely

Paths, working directories, and pathlib

with blocks, encoding, newline handling, and csv.DictReader

Schema checks, row counts, and source metadata

Malformed rows, delimiters, and immutable raw inputs

Practice, retrieval, and analyst judgment

Day 10: Summaries Before Charts

Count, sum, min, max, mean, and median

Frequency tables, proportions, and denominator labels

Sorting, top-N, ties, and the long tail

Small samples, missing values, and hidden variation

Practice, retrieval, and analyst judgment

Day 11: First Evidence Chart

Question-first chart selection

Matplotlib figure, axes, marks, labels, and scales

Bar charts and histograms from checked summaries

Truncated axes, crowded labels, and distorted evidence

Practice, retrieval, and analyst judgment

Day 12: Phase Project — Heat Access Brief

Scope, user, decision, grain, and data dictionary

Python cleaning and summary workflow with assertions

One table and two charts for distinct questions

Recommendation, uncertainty, limitations, and reproducible README

Phase gate: independent delivery and transfer

Neighbourhood Cooling-Centre Access Brief

Phase Complete!