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| Epochs and overfitting |
Introduction |
| Spark environments and options |
Introduction |
| "Extract, Transform, Load" (ETL) and " Extract, Load, Transform" (ELT) processes |
Introduction |
| Evaluating a ML model with BigQuery ML |
Introduction |
| Early stopping in ML |
Introduction |
| Principles of ethical and responsible ML (selection bias, confirmation bias, automation bias, model fairness) |
Introduction |
| Google Kubernetes Engine (GKE) |
Introduction |
| Apache hadoop and hadoop ecosystem |
Introduction |
| XGBoost (Extreme Gradient Boosting) |
Introduction |
| Exploratory data analysis (EDA) |
Introduction |
| Semantic Segmentation Using U-Net with EfficientNet and Pixelshuffle |
Introduction |
| Regression evaluation metrics |
Introduction |
| Spotify and Evernote |
Introduction |
| L1 Loss (Absolute Loss or Mean Absolute Error (MAE)) |
Introduction |
| Evaluation (Precision and Recall) in Text classification with Naive Bayes |
Introduction |
| Independence (independent events) versus dependence (dependent events) in ML |
Introduction |
| Existential Quantification |
Introduction |
| Feature engineering |
Introduction |
| Knowledge Engineering in ML |
Introduction |
| Entailment in ML |
Introduction |
| Draw smiling face emoji |
Introduction |
| One hot encoding |
Introduction |
| Evaluating process in ML |
Introduction |
| Mean squared error (MSE) (L2 loss function, Euclidean loss) and root mean squared error (RMSE) |
Introduction |
| Add padding/black/colored edge to images |
Introduction |
| Machine learning example step-by-step (wafer fail analysis) |
Introduction |
| Machine learning example step-by-step (prediction of house price) |
Introduction |
| Calibrate and put a scale bar, and draw a line segment on an image / detect a scale bar/scalebar calibration by clicking the start and end of the scale bar on desktop |
Introduction |
| Crowd’s error |
Introduction |
| Clean clipboard and/or check if clipboard is empty |
Introduction |
| .norm() (Taxicab Norm, Manhattan Norm, Euclidian Norm and Vector Max Norm) |
Introduction |
| Examples of matplotlib (image/data) visualizations |
Introduction |
| Comparison between steps and epochs in TensorFlow |
Introduction |
| find_element(By.XPATH, "") |
Introduction |
| find_element(CSS_SELECTOR, " ") |
Introduction |
| Extract the least/most frequency/duplicate/occurrence element in a list |
Introduction |
| t-SNE (t-distributed stochastic neighbor embedding, from sklearn.manifold import TSNE) |
Introduction |
| train_and_evaluate |
Introduction |
| tf.estimator |
Introduction |
| Comparison between Keras and Estimators (tf.estimators) |
Introduction |
| end( ) in TensorFlow |
Introduction |
| early_stopping.stop_if_no_decrease_hook |
Introduction |
| export_savedmodel |
Introduction |
| Feature extractions from wafers |
Introduction |
| Feature extraction using radon transform |
Introduction |
| Use __name__ to control execution of the code |
code |
| Create a function called main() to contain the code you want to run/execution |
code |
| Automation of EELS data extraction from DigitalMicrograph |
Introduction |
| Enlarge a window to maximum in size |
Introduction |
| Launch the existing opened application if there is or start a new one if there is not |
Introduction |
| Table of Excel shortcut hotkeys |
Introduction |
| Work (read, write, insert and delete rows and columns, and merge and unmerge cells, shift/move cell values) in Excel sheets |
Introduction |
| Calculation in an Excel Sheet, Style, Bold, and Color |
Introduction |
| Work with/insert images into excel sheets |
Introduction |
| Bind Python functions and methods to events (similar to if loops) |
Introduction |
| Quit/exit/stop a process (including by pressing a letter) |
Introduction |
| pop-up window for input/enter entry |
Introduction |
| Send emails in HTML and text formats |
Introduction |
| (Single and multiple enter/input) box for pop-up window |
Introduction |
| Image matching with cross correlation and overlap of template edge. In this matching process, Normalized cross-correlation with those edge images is performed. |
code. |
| Immediately invoked function expression |
code |
| Skip, remove, extract, use specific columns |
Introduction |
| Convert CSV to images, row by row, with pixel values: each row is an image |
code. |
| Check the letters and symbols starting and ending with |
code. |
| Create an executable (.exe) file from a Python script |
Introduction |
| File name, folder name. {}{}....format. Manipulation of file and folder names (rename file name and folder name): i)Rename the file, and then open the file. If the folder exists, then no file will be copied, but the file will still be opened. ii) Print and export the folder names and file names (with or without extensions) from a folder into a text file. iii) csv2image filename. |
Introduction |
| Check if a file/folder exists or not (Cannot find a specific file/folder? a specific folder in the path? select specific folders to form a string, split a dos path into its components, and then print the list, or check files with extension) |
Introduction |
| Access elements in a dictionary and subdictionary |
Introduction |
| Access elements in a list and sublist |
Introduction |
| Set default programs by file extensions and by file types and programs on Windows |
Introduction |
| Numpy: Access the element at the second row, the third entry, access a specific row or a column, access some elements (submatrix), or replace/modify an element in the array, print a transfer of an array, access array under conditions or filtering |
Introduction |
| Numpy: Access the element at the second row, the third entry, access a specific row or a column, access some elements (submatrix), or replace/modify an element in the array, print a transfer of an array, access array under conditions or filtering |
Introduction |
Handle NaN value in DataFrame, replace empty cells with ...
|
Introduction |
| Count the times of repeated excutions |
code |
| Save key and escape (ESC) key |
code. code. |
| Draw an arrow segment pointing from the start point to the end point in an image. |
code. |
| Computing equations and formulas with Python |
Examples. Numerical integration at code. |
| Open folders and explorer |
Introduction |
| Set the output image to zero everywhere except my mask (color filter), and display red, green, and blue (RGB) channels of an image. |
code, code. |
| Remove letters or characters on either side (both left and right sides) and stops when neither such letters no characters on either side |
code |
| Extract three blue, green, red images from a color image or grey image, or convert RGB (color) image into three blue, green, red images |
code |
| Find edges of images |
code, Introduction |
| Sending emails |
code |
| Find elements on a webpage |
Introduction |
| Summary of working on ppt |
Introduction |
| Add a new slide into an existing ppt, or work on existing slides |
Introduction |
| Draw lines, elbow connectors and arrows in a ppt |
Introduction |
| Check if file exists or not (Cannot find a specific file?) |
Introduction |
| Check if a list is empty or not |
Introduction |
| Remove an item/element from a list |
Introduction |
| Check if an item/element is in a list or not |
Introduction |
| Work with (e.g. open) all/every files and subfolders/subdirectory in a folder |
Introduction |
| Check file existence with partial filename |
Introduction |
| Empty and None |
Introduction |
| Add/insert a column into an existing csv file |
Introduction |
| Monitor specific new files and execute the file |
Introduction |
| Check whether a file is empty or not |
Introduction |
| Circular dependencies in Python execution |
Introduction |
| Watchdog for monitoring specific file or files with specific extension |
Introduction |
| Watchdog for monitoring specific file or files with specific extension, and then run/execute another file from watchdog |
Introduction |
| Find files with a specific file extension/type or with file names ending with specific characters |
Introduction |
| Execute scheduled jobs (time-schedule) |
Introduction |
| Delete the entire directory and/or all the files in the directory/folder |
Introduction |
| List all files and directories which has specific files or files with specific extensions |
Introduction |
| break and functions to exit a loop: Stop the loop, e.g. while loop immediately. code1, code2 |
Introduction. |
Global access to a local variable inside a function from outside of the function externally
|
Introduction |
| Search/extract/find text on an image |
Introduction |
| Extract text/check specific text from multiple powerpoint files (Some methods can extract text from most of the document extensions such as pptx and pptm) |
Introduction |
| Add a new slide into an existing ppt, or work on existing slides, check the existence of a pptx file, if does not exist then create it |
Introduction |
| Limit event/action numbers in the event List, then stop |
Introduction |
| Get pixel location/coordinates on an image using mouse click/events |
Introduction |
| Email providers and their SMTP servers |
Introduction |
| Send emails through outlook |
Introduction |
| Find the file names of the images in a pptx, (and then save/extract the image as a file) |
Introduction |
| Break/exit/skip a function/code line after a certain time |
Introduction |
| Keyword extraction methods from documents in Natural Language Processing (NLP) |
Introduction |
| Ranking and votes of essential/most important skills for data analysts |
Introduction |
| Extract pdf pages to form new pdf files |
Introduction |
| Comparison of qualifications and skills between data science manager, engineering and scientist |
Introduction |
| Extract a mask from an image with a threshold |
Introduction |
| Excursion wafer |
Introduction |
| Fault analysis/PFA (Physical Failure Analysis) time and efficiency |
Introduction |
| Extract a table from a webpage |
Introduction |
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| Bellman expectation and Bellman optimality equations |
Introduction |
| Trade-off between exploration and exploitation, and epsilon(ε-) greedy exploration |
Introduction |
| Cost (expense) and speed (fastest and slowest) of computation in ML |
Introduction |
Reinforcement learning
|
Introduction |
| Electroencephalogram cap (EEG cap) for brain |
Introduction |
| Maximum Likelihood Estimation (MLE) of single Gaussian (normal) distribution |
Introduction |
| Expectation-Maximization (EM) algorithm working in Gaussian Mixture Models (GMMs) |
Introduction |
| Expectation-Maximization (EM) algorithm |
Introduction |
Density estimation algorithms in ML
|
Introduction |
| ML example: face recognition algorithm |
Introduction |
| Learning algorithm (ensemble learning) and pipeline |
Introduction |
| Example of building robot (self-driving) systems with automated ML |
Introduction |
| Experiences of developing machine learning algorithms |
Introduction |
| Example of ML debugging: Anti-Spam |
Introduction |
| Exploding gradients in ML |
Introduction |
| Propagation equations |
Introduction |
| Edge detection of images in neural network |
Introduction |
| Batch Gradient Descent (BGD), Stochastic Gradient Descent (SGD), Mini-Batch Gradient Descent, Batch Stochastic Gradient Descent, Momentum, (Adagrad, Adadelta, RMSprop), and Adam (Adaptive Moment Estimation) |
Introduction |
Neural network vs. end-to-end learning vs. black box model
|
Introduction |
| Extract/confirm any substrings with any pattern (e.g. dot (.)) |
Introduction |
| Ensembling in ML |
Introduction |
| Ensemble of decision trees |
Introduction |
| Comparisons among Manual Search, Vertex Vizier, AutoML and Early stopping on google cloud |
Introduction |
| Generalization risk/generalization error versus empirical risk |
Introduction |
| Error excess |
Introduction |
| Difference between estimation and approximation errors |
Introduction |
| Extract the index of a string element in a list |
Introduction |
| Estimation error |
Introduction |
| Approximation error |
Introduction |
| Bayes error/Bayes risk/Bayes rate/irreducible error |
Introduction |
| Validation error |
Introduction |
| Statistical efficiency |
Introduction |
| Learning Algorithm (estimator) |
Introduction |
| Training score/training error |
Introduction |
| Training error versus model complexity |
Introduction |
| "Norm" of parameters, and L1 Norm (Manhattan Norm) and L2 Norm (Euclidean Norm) |
Introduction |
| Mathematical equations, formulas and inequalities used in machine learning |
Introduction |
| Multinomial Event Model |
Introduction |
| Apple Neural Engine (ANE) |
Introduction |
| Google's Edge TPU hardware |
Introduction |
| Optimization of energy efficiency in machine learning systems |
Introduction |
| Energy consumption in computation of machine learning |
Introduction |
| Single parameter estimation versus multiple parameter estimation |
Introduction |
| Parameters, features and examples in ML |
Introduction |
| Probability density function (PDF): comparisons between (normal (gaussian) distribution, uniform distribution, exponential distribution and poisson distribution) |
Introduction |
| Exponential Family: Parameter, Sufficient Statistic, Natural Parameter, Base Measure and Log-Partition Function (Bernoulli distribution and Gaussian distribution) |
Introduction |
| Likelihood and maximum Likelihood estimation (MLE) |
Introduction |
Comparison between mean squared error (MSE), absolute error (L1 Loss) and fourth-power loss
|
Introduction |
| Comparison between L1 Regularization and L1 Loss (absolute loss or mean absolute error (MAE)) |
Introduction |
| Kernel density estimation (KDE) |
Introduction |
| Transpose of vector and matrix and their equations |
Introduction |
| Input data (sample and feature) (multiple and single sample/example) |
Introduction |
| Training Exmaple (x, y) |
Introduction |
| Eigenvectors/eigenvalues |
Introduction |
| Stacking/stacked ensembling |
Introduction |
| Discretization error |
Introduction |
| Generalization Error/generalization risk/Generalization Loss/Test Error/Expected Error of Hypothesis/Risk |
Introduction |
| Epsilon cover/ε-cover/epsilon-net |
Introduction |
| Epoch in ML |
Introduction |
| Epochs and sample size |
Introduction |
| Empirical loss/training loss |
Introduction |
| Empericial loss versus population loss |
Introduction |
| Cross entropy (log loss/logistic loss) |
Introduction |
| Empirical Risk Minimization (ERM) |
Introduction |
| Taylor expansion |
Introduction |
| Excess risk |
Introduction |
| Check if a variable does exist/is assigned/defined |
Introduction |
| Expected risk (population risk, expected value of loss or error) |
Introduction |
| BERTScore/BERT (Bidirectional Encoder Representations from Transformer) |
Introduction |
| Evaluation of accuracy in machine learning process |
Introduction |
| Percentages of information received through different senses (eye, nose, ear and hand feeling) |
Introduction |
| RSquare (R^2) versus RASE (Root Average Squared Error) |
Introduction |
| Misclassification rate (classification error rate or error rate) in machine learning |
Introduction |
| Elastic Net |
Introduction |
| Automatically restart script execution after it breaks/fails/error |
Introduction |
| DataFrame workflow: Drop/delete rows with empty cells in a column, Sort DataFrame by time/date order |
| Check if a file exists again (double check) |
Introduction |
| EOFError |
Introduction |
| Rapid Automatic Keyword Extraction (RAKE) |
Introduction |
| Call/run/execute JMP from Python |
Introduction |
| Extract elements from a list (different way from removing elements to get part of the list) |
Introduction |
| Keyword extraction methods |
Introduction |
| Extract the first or last N letters from a string |
Introduction |
| BERTScore (Bidirectional Encoder Representations from Transformer) |
Introduction |
| Access and use SQL Database on SSMS (Microsoft SQL Server Management Studio Express) with pyodbc |
Introduction |
| Access and use SQL Database on SSMS (Microsoft SQL Server Management Studio Express) with pyodbc: localhost, insert rows, update, count updated, delete rows, comparision between extract data by Python and SQL itself |
Introduction |
| Check existence of phrase on text file line-by-line |
Introduction |
| Check if a string is empty, NaN value or space only |
Introduction |
| from keyboard import is_pressed (Esc, check pressed key) |
Introduction |
| Remove empty strings from list of strings |
Introduction |
| Remove the substring after the first or last character "::" in a given string, or extract the substring between the first and last "::" |
Introduction |
| |
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| Check if a key exists in a dictionary |
Introduction |
| IDLE (integrated development and learning environment) and integrated development environment (IDE) |
Introduction |
| hyperspy application in STEM, EDS, and EELS analysis |
Introduction |
| Check if an element in a sublist of a list |
Introduction |
| Execute a command on Command Prompt of Windows |
Introduction |
| Get an element from a set |
Introduction |
| Check if two lists have the same elements |
Introduction |
| Find common/different elements/items between two lists/sets |
Introduction |
| "@echo off" and "pause" in Command Prompt Window |
Introduction |
| Create a log (log.log) file to monitor script execution |
Introduction |
| Automatically restart script execution after it breaks/fails/error |
Introduction |
| Extract elements from a list (different way from removing elements to get part of the list) |
Introduction |
| Plot graph/figure/image from CSV file/DataFrame by removing/hiding blank/empty cells with axis range (plt.xlim()) |
Introduction |
| Skip/replace empty cells from DataFrame/CSV file |
Introduction |
| Copy a file or all files (with os.mkdir) to save to somewhere (create a directory first if it does not exist) |
Introduction |
| Inside/outside edges/margins of plotted images |
Introduction |
| Summary/templates/examples of pptx and PowerPoint format |
Introduction |
| Count how many empty strings in a list |
Introduction |
| RegEx (Regular Expression) (characters to check if a string contains a specified search pattern, remove double spaces, and clean texts) |
Introduction |
| Extract substrings between brackets (including brackets) |
Introduction |
| Extract any substrings with any pattern |
Introduction |
| Get username and encoded password with getpass or or base64 |
Introduction |
| Machine learning applications in electron microscopy |
Introduction |
Compare string entries/cells/elements of columns in different dataframes
|
Introduction |
| Find the same elements in columns in two separate dataframes and then merge them |
Introduction |
Different behavior of automation execution (e.g. pyautogui) locally or remotely through internet
|
Introduction |
| Module import and execution/run are skipped during script execution |
Introduction |
| |
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| Electrical circuit simulations |
|
| ◆ |
NgSpice/PySpice |
|
| ◆ |
Switches simulations |
|
| ◆ |
Diodes simulations |
|
| ◆ |
Electrical characteristics of the MOS capacitor |
Introduction |
| |
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| Embeddings |
Introduction |
| ◆ |
Image embeddings |
Introduction |
| ◆ |
Sentence, text, word and document embeddings |
Introduction |
| |
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| try and except |
Introduction |
| BaseException |
Introduction |
| Exception |
Introduction |
| ◆ |
exception Exception: Automatically restart script execution after it breaks/fails/error |
Introduction |
| ◆ |
ArithmeticError (arithmeticException) |
Introduction |
| |
✔ |
OverflowError (too large to store) |
Introduction |
| |
✔ |
FloatingPointError |
Introduction |
| |
✔ |
ZeroDivisionError |
Introduction |
| ◆ |
LookupError (string index) |
Introduction |
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✔ |
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✔ |
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✔ |
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✔ |
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| ◆ |
AttributeError |
Introduction |
| ◆ |
EOFError |
Introduction |
| ◆ |
OSError |
Introduction |
| |
✔ |
PermissionError (E.g. file cannot be written when it is open) |
Introduction |
| |
✔ |
FileExistsError |
Introduction |
| |
✔ |
FileNotFoundError |
Introduction |
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✔ |
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✔ |
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✔ |
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Continue script execution no matter whether some try fails or not (finally, always executes) or else |
Introduction |
| ◆ |
exception KeyboardInterrupt |
Introduction |
| |
✔ |
exception KeyboardInterrupt: Raised when the user hits the interrupt key (normally Control-C or Delete). |
Introduction |
| |
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| ◆ |
except ValueError (exception if it is not an integer) |
Introduction |
| ◆ |
|
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| ◆ |
except ImportError |
Introduction |
| ◆ |
except TypeError |
Introduction |
| ◆ |
except win32gui.error |
Introduction |
| ◆ |
except ... as -- Exception |
Introduction |
| ◆ |
except OSError |
Introduction |
| ◆ |
from retrying import retry |
Introduction |
| ◆ |
Script execution limited by retry time |
Introduction |
| ◆ |
Retry a number of times/infinite retrying before exception or fail |
Introduction |
| ◆ |
except SomeSpecificException |
Introduction |
| |
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| Skip/remove empty rows (row-by-row) in DataFrame/csv |
Introduction |
| Delete the column/row in a CSV file if they are empty or less than a number (or header/index only) |
Introduction |
| |
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| Data cleaning examples in csv files |
Introduction |
| eval() and exec() |
Introduction |
| __add__, __call__, __contains__, __delitem__, __delattr__, __eq__, __enter__, __ge__, __getattribute__, __getnewargs__, __getattr__, __getitem__, __gt__, __hash__, __reduce__, __iadd__, __imul__, __init_subclass__, __index__, __int__, __invert__, __new__, __neg__, __reduce_ex__, __reversed__, __rmul__, __radd__, __rand__, __rdivmod__, __rfloordiv__, __rlshift__, __rmod__, __ror__, __round__,__rpow__, __rrshift__, __rshift__, __rsub__, __rtruediv__, __rxor__, __dir__, __doc__, __divmod__, __iter__, __le__, __lt__, __len__, __ne__, __repr__, __setattr__, __setitem__, __sizeof__, __lshift__, __sub__, __subclasshook__, __str__ |
Introduction |
| Estimate the file size in memory before saving to PC |
Introduction |
| Add letter/commas/numbers/characters to the end/beginning of strings in a list |
Introduction |
| Remove string 0s from the back/end of a list until non-zero values |
Introduction |
| Duplicate/repeat the same words/elements in a string/list |
Introduction |
| Comparison between decision tree, random forest and XGBoost (extreme gradient boosting) |
Introduction |
| Convert a floating-point number (decimal) to exponential format |
Introduction |
| Plot workflow: Create new empty column in DataFrame, Move the cells in a column to another column under certain condition, Select specific columns for scatter plot |
| Set logarithmic scale (exponential) for y-axis in plots |
Introduction |
| Embed/hide codes or markers into HTML files |
Introduction |
| Search/extract all the 4-digit numbers (with and without extension) from a given text |
Introduction |
| Output data if any or same element in a string are in two lists |
Introduction |
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| DataFrame.equals() |
CSV: Confirm if the two csv files are the same or not: code. |
| expand=True |
CSV: (code). |
| escapechar |
CSV: string, to specify how to escape quoted data |
| encoding |
CSV: a string representing the encoding to use for decoding unicode data, e.g. ’utf-8‘ or
’latin-1’. Full list of Python standard encodings |
| error_bad_lines |
CSV: if False then any lines causing an error will be skipped bad lines |
| encoding |
CSV: a string representing the encoding to use if the contents are non-ASCII, for python versions prior
to 3 |
| escapechar |
CSV: Character used to escape sep and quotechar when appropriate (default None) |
| engine |
CSV: code. |
| enter |
Press the enter key or add "\n" in .typewrite function. Introduction |
| if-else |
if <test condition>:
<block if the test condition is true>
else:
<block if the test condition is not true>
If there are multiple else statements, then the second else is taken
along with the nearest if. code1, code2, code3, code4. |
| Difference between if and if-else |
Group 1: if and if-else. |
| if else ladder |
"else" covers all the cases other than "if".
if <test condition>:
< The task to be performed if the condition 1 is true>
elif <test 2>:
<The task to be performed if the condition 2 is true>
elif <test 3>:
<The task to be performed if the condition 3 is true>
else:
<The task to be performed if none of the above condition
is true>
It is used when there are multiple conditions and the outcomes decide the action. Here, a switch is used in the case where different
conditions lead to different actions.. |
| If ... elif ... |
Introduction. "elif" is a short word of "else if" and can have as many as "elif" as you need. code. |
| else |
Introduction. code1, code2. |
| else in for loop |
Introduction |
| sys.exit() |
Allows the developer to exit from Python. The exit function takes an optional argument, typically an integer, that gives an exit status. Zero is considered a “successful termination”. (code) |
easygui |
| import easygui |
Code. |
| easygui.egdemo() |
Code. |
| import easygui as g |
Code. |
| g.fileopenbox |
Code |
| |
| elif |
If the previous conditions were not true, then try this condition. code |
| from pptx.enum.shapes import MSO_AUTO_SHAPE_TYPE |
(code) |
| class watchdog.events.FileSystemEvent(src_path) |
Immutable type that represents a file system event that is triggered when a change occurs on the monitored file system.
event_type = None ::
The type of the event as a string.
is_directory = False ::
True if event was emitted for a directory; False otherwise.
src_path ::
Source path of the file system object that triggered this event. |
| class watchdog.events.FileSystemMovedEvent(src_path, dest_path) |
watchdog.events.FileSystemEvent :: File system event representing any kind of file system movement. dest_path ::
The destination path of the move event. |
| class watchdog.events.FileMovedEvent(src_path, dest_path) |
Bases: watchdog.events.FileSystemMovedEvent :: File system event representing file movement on the file system. |
| class watchdog.events.DirMovedEvent(src_path, dest_path) |
Bases: watchdog.events.FileSystemMovedEvent ::
File system event representing directory movement on the file system. |
| class watchdog.events.FileModifiedEvent(src_path) |
Bases: watchdog.events.FileSystemEvent :: File system event representing file modification on the file system. |
| class watchdog.events.DirModifiedEvent(src_path) |
Bases: watchdog.events.FileSystemEvent :: File system event representing directory modification on the file system. |
| class watchdog.events.FileCreatedEvent(src_path) |
Bases: watchdog.events.FileSystemEvent :: File system event representing file creation on the file system. |
| class watchdog.events.DirCreatedEvent(src_path) |
Bases: watchdog.events.FileSystemEvent :: File system event representing directory creation on the file system. |
| class watchdog.events.FileDeletedEvent(src_path) |
Bases: watchdog.events.FileSystemEvent :: File system event representing file deletion on the file system. |
| class watchdog.events.DirDeletedEvent(src_path) |
Bases: watchdog.events.FileSystemEvent :: File system event representing directory deletion on the file system. |
| class watchdog.events.FileSystemEventHandler |
Base file system event handler that you can override methods from. |
| class watchdog.events.PatternMatchingEventHandler(patterns=None, ignore_patterns=None, ignore_directories=False, case_sensitive=False) |
| watchdog.events.FileSystemEventHandler |
Matches given patterns with file paths associated with occurring events. |
| class watchdog.events.RegexMatchingEventHandler(regexes=['.*'], ignore_regexes=[], ignore_directories=False, case_sensitive=False) |
| watchdog.events.FileSystemEventHandler |
Matches given regexes with file paths associated with occurring events. |
| class watchdog.events.LoggingEventHandler |
Bases: watchdog.events.FileSystemEventHandler
Logs all the events captured. |
| class watchdog.events.LoggingEventHandler |
Bases: watchdog.events.FileSystemEventHandler
Logs all the events captured. |
| class watchdog.observers.api.EventQueue(maxsize=0) |
| class watchdog.observers.api.EventEmitter(event_queue, watch, timeout=1) |
| class watchdog.observers.api.EventDispatcher(timeout=1) |
| event_queue |
The event queue which is populated with file system events by emitters and from which events are dispatched by a dispatcher thread. |
watchdog.observers.api.EventDispatcher |
Base observer. |
| emitters |
Returns event emitter created by this observer. |
| watchdog.events |
(code) |
| math.e |
Returns the mathematical constant e (2.718281 . . .). |
| math.exp() |
Returns e raised to the power x, where e is the base of natural logarithms. |
| math.expm1() |
|
| math.erf() |
|
| math.erfc() |
|
| endswith() and startswith() |
Introduction. Returns True (or False) if a string ends (or does not end) with the specified suffix. code. (code). |
| event.src_path |
(code) |
| extend |
|
| os.path.exists() |
Check the exist of a file with a full path and name (cannot be a partial name). (code) |
| Eli5 |
Most often the results of machine learning model predictions are not accurate, and Eli5 machine learning library built in Python helps in overcoming this challenge. It is a combination of visualization and debug all the machine learning models and track all working steps of an algorithm. |
| end= |
Print without a default line break at the end, namely to get rid of the line break at the end. Introduction. code. code. code |
| einsum(subscripts, *operands[, out, dtype, …]) |
Evaluates the Einstein summation convention on the operands. |
| einsum_path(subscripts, *operands[, optimize]) |
Evaluates the lowest cost contraction order for an einsum expression by considering the creation of intermediate arrays. |
| linalg.eig(a) |
Compute the eigenvalues and right eigenvectors of a square array. |
| linalg.eigh(a[, UPLO]) |
Return the eigenvalues and eigenvectors of a complex Hermitian (conjugate symmetric) or a real symmetric matrix. |
| linalg.eigvals(a) |
Compute the eigenvalues of a general matrix. |
| linalg.eigvalsh(a[, UPLO]) |
Compute the eigenvalues of a complex Hermitian or real symmetric matrix. |
Solving equations and inverting matrices |
| linalg.solve(a, b) |
Solve a linear matrix equation, or system of linear scalar equations. |
| linalg.tensorsolve(a, b[, axes]) |
Solve the tensor equation a x = b for x. |
| linalg.lstsq(a, b[, rcond]) |
Return the least-squares solution to a linear matrix equation. |
| linalg.inv(a) |
Compute the (multiplicative) inverse of a matrix. code. |
| linalg.pinv(a[, rcond, hermitian]) |
Compute the (Moore-Penrose) pseudo-inverse of a matrix. |
| linalg.tensorinv(a[, ind]) |
Compute the ‘inverse’ of an N-dimensional array. |
| |
| .extend() |
copy method. |
| from scipy.linalg import eigh |
Print "selected eigenvalues" and "complex ndarray": code. |
| skimage.measure.EllipseModel() |
Total least squares estimator for 2D ellipses. |
| smtp.ehlo() |
code. |
| v2.rectangle(image, start_point, end_point, color of border line, border thickness) |
border. Compute the bounding box of the contour and then draw the bounding box on an image to represent where the ROI is. code. code. code. |
| cv2.EVENT_FLAG_LBUTTON |
Mouse callback function with a single left click. code. |
| cv2.EVENT_LBUTTONDOWN |
Mouse callback function with a single left click. code. (code) |
| cv2.EVENT_FLAG_MBUTTON |
Mouse callback function with a single left click. code. |
| cv2.EVENT_LBUTTONUP |
Mouse callback function with a single left click. code. |
| cv2.EVENT_LBUTTONDBLCLK |
Mouse callback function with double left clicks. code. |
| cv2.EVENT_RBUTTONDOWN |
Mouse callback function with a single right click. code. |
| cv2.EVENT_RBUTTONUP |
Mouse callback function with a single right click. code. |
| cv2.EVENT_FLAG_RBUTTON |
Mouse callback function with a single right click. code. |
| cv2.EVENT_FLAG_CTRLKEY |
Mouse callback function with double right clicks. code. |
| cv2.EVENT_MBUTTONDOWN |
Mouse callback function with the single middle mouse click. code. |
| cv2.EVENT_MBUTTONUP |
Mouse callback function with the single middle mouse click. code. |
| cv2.EVENT_MOUSEMOVE |
Mouse move. code. |
Excel in Python |
| to_clipboard([excel, sep]) |
Attempt to write text representation of object to the system clipboard. This can be pasted into Excel, for example. |
| to_dict(*args, **kwargs) |
Convert DataFrame to dictionary. |
| to_html([buf, columns, col_space, colSpace, ...]) |
Render a DataFrame as an HTML (www, webpage) table. |
| to_sql(name, con[, flavor, schema, ...]) |
Write records stored in a DataFrame to a SQL database. |
| to_timestamp([freq, how, axis, copy]) |
Cast to DatetimeIndex of timestamps, at beginning of period |
| to_records([index, convert_datetime64]) |
Convert DataFrame to record array. |
| to_string([buf, columns, col_space, ...]) |
Render a DataFrame to a console-friendly tabular output. |
| to_dense() |
Return dense representation of NDFrame (as opposed to sparse) |
| to_excel(excel_writer[, sheet_name, na_rep, ...]) |
Write DataFrame to a excel sheet |
| to_gbq(destination_table[, project_id, ...]) |
Write a DataFrame to a Google BigQuery table. |
| to_hdf(path_or_buf, key, **kwargs) |
activate the HDFStore |
| to_json([path_or_buf, orient, date_format, ...]) |
Convert the object to a JSON string. |
| to_latex([buf, columns, col_space, ...]) |
Render a DataFrame to a tabular environment table. |
| to_msgpack([path_or_buf]) msgpack (serialize) |
object to input file path |
| to_panel() |
Transform long (stacked) format (DataFrame) into wide (3D, Panel) format. |
| to_period([freq, axis, copy]) |
Convert DataFrame from DatetimeIndex to PeriodIndex with desired |
| to_pickle(path) |
Pickle (serialize) object to input file path |
| to_sparse([fill_value, kind]) |
Convert to SparseDataFrame |
| to_stata(fname[, convert_dates, ...]) |
A class for writing Stata binary dta files from array-like objects |
| Split into multiple files |
|
| .active |
(code) |
| .value |
(code) |
| .sheetnames |
(code) |
| .save() |
(code) |
| title |
Title of a sheet. (code) |
| xlsxwriter |
(code) |
| .get_column_letter() |
(code) |
| .create_sheet('') |
(code) |
| |
| np.eye() |
General. |
| ElectricPy |
Has functions and constants related to electrical engineering. It depends on
Numpy,
Matplotlib,
Scipy,
Sympy, and
Numdifftools |
| t.end_fill() |
turtle.end_fill().
Fill the shape drawn after the last call to begin_fill(). (code) |
| execute_script("window.scrollBy(0, 250)") |
(code) |
| hotkey('e') |
Introduction |
| ESC on keyboard |
Code 27 for ESC key. Introduction |
| enumerate() |
Introduction |
| .Entry |
When a text, e.g. a name or an email address, from a user is needed, you can use an Entry widget, which works pretty much exactly like Label and Button widgets. Three main operations: .get(), .delete() and .insert(). Introduction |
| entry.delete(0, tk.END) |
Use the special constant tk.END for the second argument of .delete() to remove all text in an Entry |
| ensemble |
(code). |
| split() |
Introduction. Split a string by dots, split a file name by dots, split a file name from its extension. code. (code). |
| Emu |
Inches, Emu, Cm, Mm, Pt, and Px are base class for length classes, providing properties for converting length values to convenient units. |
| Comparison between *, .extend((), append(), =, ==, .copy() and copy.copy() for "list": changes of "list" |
Introduction |
| os.path.expanduser() |
(code). |
| os.path.expandvars() |
(code). |
| .DataFrame() |
Introduction. .drop(),
index,
columns,
axes,
dtypes,
size,
shape,
ndim,
empty,
T,
values |
| |
|
| Euclidean distance and Euclidian similarity for images |
Introduction |
| |
|
| Euclidean distance and Euclidian similarity for data and words |
Introduction |
| |
|
