course
Introduction to Python in Power BI
मध्यवर्तीकौशल स्तर
अद्यतन 10/2024कोर्स मुफ्त में शुरू करें
इसमें शामिल हैअधिमूल्य or टीमें
Power BIData Manipulation3 घंटा9 videos25 exercises2,000 एक्सपी7,530उपलब्धि का कथन
अपना निःशुल्क खाता बनाएँ
या
जारी रखने पर, आप हमारी उपयोग की शर्तें, हमारी गोपनीयता नीति को स्वीकार करते हैं और यह भी कि आपका डेटा संयुक्त राज्य अमेरिका में संग्रहीत किया जाता है।हजारों कंपनियों में कार्यरत शिक्षार्थियों द्वारा पसंद किया जाता है
दो या दो से अधिक लोगों को प्रशिक्षण देना?
DataCamp for Business को आज़माएँपाठ्यक्रम विवरण
Customize Power BI with Python
In this introduction to Python in Power BI course, you’ll use data from an overfishing study and an online retailer to learn how to use Python scripts in Power BI for data prep, visualizations, and calculating correlation coefficients.Build Custom Visuals
Specifically for building custom Python-based visuals, you will be utilizing the Seaborn package. By the end, you should feel a little more comfortable using Python in (and outside of) Power BI.Power up your Toolbox
Whether you were first a Pythonista or a Power BI power user, integrating Python into Power BI is a fantastic addition to the data toolbox. This course will demonstrate that, by using the two together, you can leverage the benefits of each, choosing the best one for the task at hand.आवश्यक शर्तें
Introduction to DAX in Power BIIntroduction to Data Visualization with Seaborn1
Getting Started with Python in Power BI
In this first chapter, you will learn the advantages and limitations of Python in Power BI as well as how to enable this capability within a workbook. You will also perform the same task using both technologies separately to build familiarity with the strengths and weaknesses of both. Power BI is a powerful tool. Python can be leveraged to make it even more powerful!
2
Missing Data and Imputation
Now that you're up and running with Python in Power BI, let's move on to another important data processing step - identifying missing data and imputation. In this chapter, you will identify missing data in a dataset using Python, then Power BI. You will then work through addressing missing data by leveraging imputation techniques.
3
Visualizations with Seaborn in Power BI
In this chapter, you will construct several Python-based visualizations, using the Seaborn package, in Power BI. Specifically, a line plot, pair plot, and joint plot. You will also learn how to interpret these visualizations to extract insights about the data. By this point, you will know some of the key differences between Python and Power BI in basic data processing steps. The next step is to visualize this data!
4
Heatmaps and Correlation Coefficients
In this chapter, you will continue evaluating the relationship between variables. This time, you will be doing so quantitatively by calculating the correlation coefficient. You will learn how to do this in Power BI then Python. Finally, you will leverage the power of Seaborn visualizations to create a correlation heatmap! By the time you finish the course, you'll be skilled in Power BI, Python, and data visualization techniques. Nice work!
Introduction to Python in Power BI
कोर्स पूरा
उपलब्धि प्रमाण पत्र अर्जित करें
इस क्रेडेंशियल को अपने लिंक्डइन प्रोफाइल, रिज्यूमे या सीवी में जोड़ें।इसे सोशल मीडिया पर और अपनी परफॉर्मेंस रिव्यू में साझा करें।
इसमें शामिल हैअधिमूल्य or टीमें
अभी दाखिला लेंजुड़ें 19 मिलियन शिक्षार्थी और आज ही Introduction to Python in Power BI शुरू करें!
अपना निःशुल्क खाता बनाएँ
या
जारी रखने पर, आप हमारी उपयोग की शर्तें, हमारी गोपनीयता नीति को स्वीकार करते हैं और यह भी कि आपका डेटा संयुक्त राज्य अमेरिका में संग्रहीत किया जाता है।