Microsoft Office Excel
Google Sheets
LibreOffice - Calc
Apple Numbers
Apache OpenOffice Calc
Zoho Sheet
EtherCalc
Gnumeric
NumPy
Pandas
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
Microsoft Office ExcelA software program created by Microsoft that uses spreadsheets to organize numbers and data with formulas and functions. It is one of the best software for daily use Microsoft Office Excel has been an absolute game-changer for me in the realm of spreadsheet applications. Whether it's managing data, creating intricate formulas, or visualizing trends, Excel stands out as a powerhouse of functionality and efficiency.
What would we do without Excel!? Sure, the online version isn't as simple as Google Sheets, they could have chosen not to localise the function names, and it's always chaos trying to consolidate multiple budget or forecast files & templates, but aside from that it's everyone's favourite spreadsheet. What you can't do in Excel isn't worth doing. Even if there's often a better way...
It is one of the best software for daily purpose.
Based on our record, NumPy seems to be more popular. It has been mentiond 107 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / about 2 months ago
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / about 2 months ago
Numpy: A library for scientific computing in Python. - Source: dev.to / 5 months ago
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 6 months ago
A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 7 months ago
Google Sheets - Synchronizing, online-based word processor, part of Google Drive.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
LibreOffice - Calc - LibreOffice Calc is the spreadsheet program you've always needed. A fork of OpenOffice.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Apple Numbers - Numbers lets you build beautiful spreadsheets on a Mac, iPad, or iPhone — or on a PC using iWork for iCloud. And it’s compatible with Apple Pencil.
OpenCV - OpenCV is the world's biggest computer vision library