Excel To PNG Python

The most useful program for a mechanical engineer will depend on your focus. However here are a handful of the most useful ones that almost every mechanical engineer would benefit from knowing Mathcad I use Mathcad constantly and I would possibly consider this the most useful of all the software I use at my job. Mathcad is good for doing math in a way that is presentable -- i.e. it's good for doing math in a report layout with formatted math s and write a VBA script to insert every .png into my document for me. This saved a ton of time. MATLAB This is an amazing analysis tool and is the programming environment of choice for mechanical engineers. MATLAB is essential for doing moreplex numerical analysis where simple math doesn't cut it and a programming solution is required. Python I have found Python to be an excellent alternative to MATLAB. Python is open-source and you can achieveparable functionality to MATLAB by installing NumPy SciPy and Matplotlib (there are other packages such as Pandas that you may also want). Python is a widely respected language and has a major following in the scientificmunity. One major advantage of Python (besides the price of free) is that it is a general purpose programming language (i.e. it is not specifically tailored to scientific programming although it is excellent for that). This means that you can use it to do many other things that you may want to do such as work with your file system or build a website. Best of luck Arthur Kirkby MechaniCalc s

The best analysis tools for mechanical engineers are Mathcad I use Mathcad constantly and I would possibly consider this the most useful of all the software I use at my job. Mathcad is good for doing math in a way that is presentable -- i.e. it's good for doing math in a report layout with formatted math s and write a VBA script to insert every .png into my document for me. This saved a ton of time. MATLAB This is an amazing analysis tool and is the programming environment of choice for mechanical engineers. MATLAB is essential for doing moreplex numerical analysis where simple math doesn't cut it and a programming solution is required. Python I have found Python to be an excellent alternative to MATLAB. Python is open-source and you can achieveparable functionality to MATLAB by installing NumPy SciPy and Matplotlib (there are other packages such as Pandas that you may also want). Python is a widely respected language and has a major following in the scientificmunity. One major advantage of Python (besides the price of free) is that it is a general purpose programming language (i.e. it is not specifically tailored to scientific programming although it is excellent for that). This means that you can use it to do many other things that you may want to do such as work with your file system or build a website. Best of luck Arthur Kirkby MechaniCalc s

The most useful software for a mechanical engineer will depend on your focus. However here are a handful of the most useful software packages that almost every mechanical engineer would benefit from knowing Mathcad I use Mathcad constantly and I would possibly consider this the most useful of all the software I use at my job. Mathcad is good for doing math in a way that is presentable -- i.e. it's good for doing math in a report layout with formatted math s and write a VBA script to insert every .png into my document for me. This saved a ton of time. MATLAB This is an amazing analysis tool and is the programming environment of choice for mechanical engineers. MATLAB is essential for doing moreplex numerical analysis where simple math doesn't cut it and a programming solution is required. Python I have found Python to be an excellent alternative to MATLAB. Python is open-source and you can achieveparable functionality to MATLAB by installing NumPy SciPy and Matplotlib (there are other packages such as Pandas that you may also want). Python is a widely respected language and has a major following in the scientificmunity. One major advantage of Python (besides the price of free) is that it is a general purpose programming language (i.e. it is not specifically tailored to scientific programming although it is excellent for that). This means that you can use it to do many other things that you may want to do such as work with your file system or build a website. Best of luck Arthur Kirkby MechaniCalc s

Many had the following libraries listed Matplotlib plotly And would like to add pyecharts (I love this one).nDocumentation A Python Echarts Plotting Library # nThere is both javascript ( ECharts Demo s ) and python support and also ability to fine tune everything from font to colors of the graph (although would require you to override colors using inheritance or monkey patching). Pros italic Support for javascript and python. Lot of graphs varieties to choose from. And many more Cons italic Dependency on phantom js for exporting it as PDF or png files (can be set up easily though) Its a pretty solid library to look into and I would definetly rmend it. Installation notes italic 1. install pyecharts $ pip install pyecharts code $ pip install pyecharts-snapshot code 2. Install phantomJS $ sudo yum install fontconfig free free-devel fontconfig-devel libstdc++2 code code $ wget s code code $ sudo mkdir -p code code $ bzip2 -d code code $ sudo tar -xvf --directory --stripponents 1 code code $ sudo ln -s code Verify the installation of phantomJS $ phantomjs code Happy learning )

There are many ways to do this so I'm only going to show you a way italic that you can do this. First you'll need to install pillow italic which is an easier to use italic API for the Python Imaging Library (PIL). pip install pillow code Then it's just as simple as opening the code = code code #open a file to write the pixel data code with open('' 'w+') as f code ('RGBn') code code #read the details of each pixel and write them to the file code for x in range() code for y in range() code r = pixxy code g = pixxx1 code b = pixxx2 code ('12n'.format(rgb)) code Keep in mind that an email has a lot of pixels in it! In the example above my 3x3 image will generate 9 lines in the table because that's how many pixels there are.

I will skip the basic programming stuff such as object-oriented programming data s operators etc. Instead let focus on the functional perspective on using Python for different data science tasks to gather clean explore model italic and present italic the results. Gather data - You need a connector interface to gather data from RDBMS e.g. pymssql - pymssql documentation or PyMySQL s for RDBMS and PyMongo Documentation s for NoSQL e.g. Mongo. If you gather data from a file you need to know the I in Python using 7. Input and Output s in particular how to use read readlines() and iterate each line using for loop. If you are reading from Excel or CSV file you may use a library like Python Data Analysis Library s . If you want to gather data from web applications using API you need Requests HTTP for Humans22 tomunicate with the servers and maybe 18.2. json - JSON encoder and decoder - Python documentation s in case you want to perform some manipulation. If the website you are accessing does not provide an API you have to manually scrape the content and parse it with Beautiful Soup Documentation s . Explore data - We check the shape look for significant patterns anomalies and any other information that helps us to understand the dataset better. We start with Pandas to read our data into a data frame for us to perform descriptive analysis using mathematical calculations. Then we use charting library such as Python plotting - Matplotlib documentation s Wee to Bokeh s or seaborn statistical data visualisation s to visualise data and identify relationships between variables Presentation - You can use the charting library as mentioned in #3 to produce charts and export them as PNG file for use in website or presentations. Use plotly s to make your chart interactive. Use the SQL connectors from #1 if you need to write data to the database and use Flask or Django ( The Web framework for perfectionists with deadlines s ) to publish your results as a web application or web API. ordered-list p Make sure you also learn List Comprehensions in Python s it is a helpful technique in Python that helps save tons of time and make your code much readable just that it is not often mentioned in the data science con.

Steps Step 1 The first step is to import the xlrd library. We use xlrd package to read the data from Excel spreadsheets. If xlrd library is not installed you can download from here s . import xlrd code Step 2 In this step we will open an Excel file in the current directory. ExcelFileName= '' code workbook = (ExcelFileName) code worksheet = (Sheet1) # We need to read the data code #from the Excel sheet named Sheet1 code Step 3 In the current example we know that the data is saved in Column A and Column B. However if we have to read multiple rows and columns and donot exactly how many rows and columns we need to first obtain the number of rows and columns num_rows = #Number of Rows code num_cols = #Number of Columns code Step 4 The last step is to parse through each row and each column and read the data in the current cell. result_data = code for curr_row in range( num_rows 1) code row_data = code for curr_col in range( num_cols 1) code data = (curr_row curr_col) # Read the data in the current cell code #print(data) code (data) code (row_data) code Credits Stack Overflow - Where Developers Learn Share & Build Careers Creating Excel files with Python and XlsxWriter s

Read my answer to another similar question here - Sarthak Jain's answer to What are some good uses for AWS Lambda? answer aid 242568774 Read our blog s to see how we are using AWS Lambda at Clappia. The beauty of AWS Lambda lies in its ability to integrate with a lot of other AWS Services. At Clappia we use AWS Lambda in the following ways - AWS Lambda with API Gateway nAt Clappia we follow a Microservices architecture in which we have separate services for managing different entities. All the functions in each of these services are implemented as functions in AWS Lambda and exposed to the front-end clients using API Gateway. AWS Lambda with Step Functions nWe use Step Functions to power the Clappia Workflows that consist of actions like sending emails mobile notifications SMS WhatsApp messages integrating with external APIs and databases some IF logic etc. All these actions are implemented in AWS Lambda. We translate these user-defined Workflows and generate a state machine in Step Functions. AWS Lambda with SNS nWe have some use cases which involve tasks that can run asynchronously without having the end-user to wait for thepletion of these such use cases we use SNS. SNS uses the Pub-Sub messaging mechanism to send messages between different Lambda functions. So when a user action happens one Lambda function performs some db updates then publishes an SNS Message and returns a response to the user. The SNS Message gets consumed by a second Lambda function that sends out an email and does some other non-critical tasks. With this approach we reduce the latencies of user-facing business logic by off-loading a portion of the logic to other Lambda functions. AWS Lambda with S3 nS3 file uploads can serve as triggers for Lambda functions. We use it for two use casesnnImage resize High definition s is not necessary in most cases. Serving these large s. AWS Lambda with CloudWatch rules nCloudWatch events and rules can be used together with AWS Lambda to run tasks at periodic intervals or when certain CloudWatch events are triggered.