29 docs tagged with "Python"

sum, mean, median, std and var; the axis argument; why NumPy and pandas disagree on std; and handling nan.

Creating ndarrays, the six shape attributes, dtypes, and why an array is not a list.

Every chart type answers one specific question — pick the chart by starting from the question.

Filling and dropping missing values, removing duplicates, and converting types back after the fix.

if, if/else, if/elif/else, nested conditions, and the logical operators that combine them.

Measuring whether two variables move together — the correlation scale, why covariance can't be compared, and what correlation misses.

Python's four scalar and four collection types — int, float, str, bool, list, tuple, dict, set.

Mean, median, mode, range, variance, standard deviation and quartiles — what each one tells you and when it misleads.

Key/value lookup with dict, uniqueness and set algebra with set, and why keys must be immutable.

The EDA workflow — inspect, check for gaps, describe, count categories, group, and correlate.

Arithmetic operators, PEMDAS precedence, and five ways to structure the same answer.

Formatted string literals — format specs, alignment, padding, conversion flags, and debug mode.

1-D and 2-D access, why NumPy slices are views rather than copies, boolean masking, and reshape.

input() always returns a string, and print() has three parameters worth knowing — sep, end, and the values themselves.

head, tail, shape, dtypes, info and describe — the first six things to run on any new DataFrame.

The mutable sequence — methods that change it in place, sort vs sorted, the reference trap, and comprehensions.

read_csv, read_excel and read_json; writing back out; and why index=False matters.

for and while loops, range(), break and continue, the loop else clause, and nested loops.

Line, bar, histogram, scatter and pie charts with pyplot — plus figure, show and savefig.

Element-wise arithmetic, the broadcasting rules, universal functions, matrix multiplication, sorting and stacking.

Interactive charts with plotly.express — hover, zoom and pan, plus bubble charts and how to export.

Python notes from Fundamentals of AI — basics through NumPy, Pandas, and visualisation.

Statistical charts in one line — bar, count, histogram, scatter, box, violin, heatmap and pair plot.

Column selection, loc vs iloc, filtering, sorting, adding columns, groupby, merge and concat.

The two pandas structures — a labelled 1-D Series and a 2-D DataFrame — and how the index changes everything.

Indexing, the three-part slice, immutability, and the string methods worth knowing.

The immutable sequence — the trailing-comma rule, shallow immutability, unpacking, and when a tuple beats a list.

Every Python value carries its type. How to ask what that type is, and what happens when you convert between them.

What makes a Python identifier legal, the 35 reserved keywords, and the PEP 8 conventions on top.