| Topic / Command | Explanation | Example / Usage |
|---|---|---|
| Installation | Install Python packages. | python -m pip install |
| Interpreter | Invoke the Python REPL interactively. | python |
| Script Execution | Run a Python script file. | python my_script.py |
| Comments | Lines ignored by the interpreter. | # This is a comment |
| print() | Display output to stdout. | print("Hello World") |
| Variables | Automatically typed; no need for explicit declaration. | x = 42 |
| Multiple Assignment | Assign multiple variables at once. | a, b, c = 1, 2, 3 |
| Type Checking | Find the type of a variable. | type(x) → <class 'int'> |
| Type Casting | Convert between types (str, int, float, list, etc.). | int("100") → 100 |
| String Literals | Create strings with single, double, or triple quotes. | "Hello", 'Hi', """Multi-line string""" |
| String Formatting | Format strings with f-strings or format method. | f"Value is {x}" or "{}".format(x) |
| String Methods | Built-in methods for manipulation (split, lower, replace). | "Hello".upper() → "HELLO" |
| Help / Docstrings | Built-in help or docstrings. | help(str) or print(str.doc) |
| Topic / Statement | Explanation | Example / Usage |
|---|---|---|
| if, elif, else | Conditional statements. | if x > 0: ... elif x == 0: ... else: ... |
| for loop | Iterate over a sequence or iterable. | for i in range(5): print(i) |
| while loop | Repeat until a condition becomes False. | while x < 5: x += 1 |
| break | Exit a loop prematurely. | if condition: break |
| continue | Skip to next iteration of a loop. | if condition: continue |
| pass | Do nothing (placeholder). | if condition: pass |
| range() | Generate a sequence of integers. | range(0, 10, 2) → 0, 2, 4, 6, 8 |
| else (on loops) | Executes if no break occurs in a loop. | for i in range(5): ... else: print("Done") |
| Structure / Topic | Explanation | Example / Usage |
|---|---|---|
| List | Ordered, mutable collection. | my_list = [1, 2, 3] |
| List Comprehension | Compact way to build lists. | [x**2 for x in range(5)] → [0,1,4,9,16] |
| Tuple | Ordered, immutable collection. | my_tuple = (1, 2, 3) |
| Set | Unordered, unique elements. | my_set = {1, 2, 3} |
| Dict | Key-value pairs, mutable. | my_dict = {"key": "value"} |
| Access Dict Values | Retrieve or set dictionary values by key. | my_dict["key"] |
| Dict Methods | get(), keys(), values(), items(). | my_dict.get("key", default_val) |
| Adding to List | Use append() or extend(). | my_list.append(4) |
| Removing from List | Use remove(value), pop(index), or del. | my_list.remove(2) |
| Slicing | Access sub-portions of sequences. | my_list[1:3] → elements at index 1 and 2 |
| Topic / Keyword | Explanation | Example / Usage |
|---|---|---|
| def | Define a function. | def my_func(a, b=0): return a + b |
| Return Values | Functions return data with return statement. | return a + b |
| Positional Arguments | Regular arguments in order. | my_func(1, 2) |
| Keyword Arguments | Specifying argument name in function call. | my_func(a=1, b=2) |
| args | Accept variable number of positional args. | def my_func(args): |
| **kwargs | Accept variable number of keyword args. | def my_func(**kwargs): |
| Lambda Functions | Anonymous functions. | my_lambda = lambda x: x2 |
| Docstrings | Document your function. | def f(x): """Does X.""" return x |
| Annotations | Type hints. | def f(x: int) -> int: return x2 |
| Concept / Keyword | Explanation | Example / Usage |
|---|---|---|
| class | Defines a new class. | class MyClass: ... |
| init | Class constructor/initializer. | def init(self, val): self.val = val |
| self | Refers to the instance within class methods. | self.val = val in init |
| Instance Method | Functions defined inside a class that operate on instance. | def method(self): return self.val |
| Class Variable | Shared across all instances. | class MyC: var=0 |
| Inheritance | Child class inherits attributes and methods from parent. | class Child(Parent): ... |
| super() | Call parent class methods/constructors. | super().init() |
| str / repr | String representation of an object. | def str(self): return f"val={self.val}" |
| @staticmethod | Method that doesn’t use self (no instance needed). | @staticmethod def foo(): return "bar" |
| @classmethod | Method that receives class (cls) as the first argument. | @classmethod def from_data(cls, data): ... |
| Concept / Keyword | Explanation | Example / Usage |
|---|---|---|
| try / except | Catch exceptions. | try: ... except ValueError: ... |
| else | Code block that executes if no exception is raised. | try: ... except: ... else: ... |
| finally | Code block that always executes. | try: ... finally: cleanup() |
| raise | Raise an exception manually. | raise ValueError("Bad value") |
| Logging with logging | Standard logging library. | import logging; logging.info("Info msg") |
| log levels | Common levels: DEBUG, INFO, WARNING, ERROR, CRITICAL. | logging.warning("Warning message") |
| Topic / Keyword | Explanation | Example / Usage |
|---|---|---|
| open() | Opens a file. | f = open("file.txt", "r") |
| read(), readline() | Read entire file or read line-by-line. | data = f.read() |
| write() | Write string data to a file. | f.write("Hello") |
| close() | Close the file when done. | f.close() |
| with statement | Context manager for file handling (auto close). | with open("file.txt", "r") as f: data = f.read() |
| modes | Common modes: 'r', 'w', 'a', 'x', 'rb', 'wb'. | open("file.bin", "wb") |
| Concept / Keyword | Explanation | Example / Usage |
|---|---|---|
| Virtualenv | Create isolated Python environments. | python -m venv venv_name |
| Activate venv (Linux) | Activate virtual environment on Linux/macOS. | source venv_name/bin/activate |
| Activate venv (Windows) | Activate virtual environment on Windows. | venv_name\Scripts\activate |
| Deactivate venv | Exit out of the virtual environment. | deactivate |
| Modules | Individual .py files with reusable code. | import my_module |
| Packages | Directories with init.py that group modules. | from my_package import my_module |
| name == "main" | Check if file is run as script or imported as module. | if name == "main": main() |
| pip freeze | List installed packages with versions. | pip freeze > requirements.txt |
| Requirements file | Reproduce environment. | pip install -r requirements.txt |
| Topic / Package | Explanation | Example / Usage |
|---|---|---|
| threading | Concurrency via threads (subject to GIL for CPU-bound code). | import threading |
| multiprocessing | True parallelism by spawning processes. | from multiprocessing import Process |
| async / await | Asynchronous I/O operations. | async def my_coro(): await something() |
| asyncio | Core library for async in Python. | import asyncio |
| GIL (Global Interpreter | Only one thread runs Python bytecode at a time. | N/A |
| Lock) |
| Concept / Function | Explanation | Example / Usage |
|---|---|---|
| import numpy as np | Conventional alias for NumPy. | import numpy as np |
| Creating Arrays | Use np.array() or various np.* methods. | arr = np.array([1,2,3]) |
| np.zeros, np.ones | Create arrays of zeros or ones. | np.zeros((2,2)), np.ones((3,3)) |
| np.arange, np.linspace | Generate ranges or evenly spaced numbers. | np.arange(0,10,2), np.linspace(0,1,5) |
| Shape | Get or set array shape. | arr.shape, arr.reshape(2,3) |
| Indexing & Slicing | Similar to Python lists but for n-dim arrays. | arr[0,1], arr[:, 0], arr[1:3, :] |
| Vectorized Ops | Elementwise operations. | arr + 2, arr * 3, arr1 + arr2 |
| Broadcasting | Automatic expansion to match shapes in operations. | arr + scalar, arr + smaller arr |
| np.sum, np.mean, etc. | Aggregations on arrays. | np.sum(arr), np.mean(arr, axis=0) |
| Matrix Multiplication | Use the @ operator or np.dot(). | arr1 @ arr2, np.dot(arr1, arr2) |
| Axis Argument | Choose dimension for operations. | np.sum(arr, axis=0) |
| np.random | Random sampling (rand, randn, randint). | np.random.rand(3,2) |
| Concept / Function | Explanation | Example / Usage |
|---|---|---|
| import pandas as pd | Conventional alias for pandas. | import pandas as pd |
| pd.Series | 1D labeled array. | s = pd.Series([1,2,3], name="Numbers") |
| pd.DataFrame | 2D labeled data structure. | df = pd.DataFrame(data, columns=[...]) |
| Reading Data | Common I/O methods (CSV, Excel, SQL). | pd.read_csv("file.csv"), pd.read_excel(...), pd.read_sql(...) |
| df.head(), df.tail() | Preview top/bottom rows of a DataFrame. | df.head() |
| df.info(), df.describe() | Get info and summary statistics. | df.info(), df.describe() |
| Indexing & Slicing | .loc (label-based), .iloc (integer-based). | df.loc[0], df.iloc[0:3, 1:4] |
| Filtering Rows | Boolean indexing. | df[df["col"] > 10] |
| df["col"] | Select a single column as a Series. | s = df["col"] |
| Adding Columns | Assign a new column directly. | df["new"] = df["a"] + df["b"] |
| Dropping | Remove rows or columns. | df.drop("col", axis=1) |
| Grouping & Aggregation | groupby and agg methods. | df.groupby("key").agg({"val": "mean"}) |
| Merging/Joining | Combine DataFrames on shared columns/index. | pd.merge(df1, df2, on="key") |
| df.apply(), df.applymap() | Apply functions to columns/rows or elementwise. | df["col"].apply(np.log) |
| df.pivot, df.pivot_table | Reshape data. | df.pivot_table(values="val", index="rowKey") |
| df.sort_values() | Sort by one or more columns. | df.sort_values("col", ascending=False) |
| Concept / Function | Explanation | Example / Usage |
|---|---|---|
| import matplotlib.pyplot as plt | Main plotting interface. | import matplotlib.pyplot as plt |
| Basic Plot | Simple line plot. | plt.plot(x, y) |
| Scatter Plot | Plot data as points. | plt.scatter(x, y) |
| Bar Plot | Plot bar chart. | plt.bar(categories, values) |
| Histogram | Distribution of data. | plt.hist(data, bins=20) |
| Labels & Titles | Add axis labels and chart title. | plt.xlabel("X"), plt.ylabel("Y"), plt.title("My Plot") |
| Show Plot | Render the figure. | plt.show() |
| Subplots | Multiple plots in a figure. | plt.subplot(2,1,1); plt.plot(...); |
| fig, ax = plt.subplots() | Object-oriented approach. | ax.plot(x, y) |
| Save Figure | Save a figure to file. | plt.savefig("plot.png") |
| Ticks & Legends | Adjust ticks or add legend. | plt.xticks(...), plt.legend() |
| Concept / Class / Function | Explanation | Example / Usage |
|---|---|---|
| import sklearn | Main machine learning library in Python. | from sklearn import datasets |
| Datasets | Built-in toy datasets (Iris, Boston, etc.). | iris = datasets.load_iris() |
| Train/Test Split | Partition data for training and testing. | from sklearn.model_selection import train_test_split X_train, X_test, y_train, y_test = ... |
| Estimators (Models) | Classes that implement fit(), predict(), transform(). | from sklearn.linear_model import LogisticRegression |
| Model Fitting | Train model on data. | model = LogisticRegression() model.fit(X_train, y_train) |
| Prediction | Predict on new or test data. | preds = model.predict(X_test) |
| Evaluation | Evaluate with common metrics. | from sklearn.metrics import accuracy_score |
| Transformers (e.g. Scaling) | Preprocessing (StandardScaler, MinMaxScaler, etc.). | from sklearn.preprocessing import StandardScaler scaler = StandardScaler().fit(X_train) |
| Pipelines | Chain transformers and estimators. | from sklearn.pipeline import Pipeline pipe = Pipeline([...]) |
| Cross-Validation | Evaluate models by splitting in multiple ways. | from sklearn.model_selection import cross_val_score |