Practical Data Analysis Using Jupyter Notebook Learn how to speak the language of data by extracting useful and actionable insights using Python.pdf
What you will learn • Understand the importance of data literacy and how to communicate effectively using data • Find out how to use Python packages such as NumPy, pandas, Matplotlib, and the Natural Language Toolkit (NLTK) for data analysis • Wrangle data and create DataFrames using pandas • Produce charts and data visualizations using time-series datasets • Discover relationships and how to join data together using SQL • Use NLP techniques to work with unstructured data to create sentiment analysis models • Discover patterns in real-world datasets that provide accurate insights
Practical Data Analysis Using Jupyter Notebook Learn how to speak the language of data by extracting useful and actionable insights using Python.pdf
What you will learn • Understand the importance of data literacy and how to communicate effectively using data • Find out how to use Python packages such as NumPy, pandas, Matplotlib, and the Natural Language Toolkit (NLTK) for data analysis • Wrangle data and create DataFrames using pandas • Produce charts and data visualizations using time-series datasets • Discover relationships and how to join data together using SQL • Use NLP techniques to work with unstructured data to create sentiment analysis models • Discover patterns in real-world datasets that provide accurate insights
BY Python 🐍 Work With Data
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Tata Power whose core business is to generate, transmit and distribute electricity has made no money to investors in the last one decade. That is a big blunder considering it is one of the largest power generation companies in the country. One of the reasons is the company's huge debt levels which stood at ₹43,559 crore at the end of March 2021 compared to the company’s market capitalisation of ₹44,447 crore.
The lead from Wall Street offers little clarity as the major averages opened lower on Friday and then bounced back and forth across the unchanged line, finally finishing mixed and little changed.The Dow added 33.18 points or 0.10 percent to finish at 34,798.00, while the NASDAQ eased 4.54 points or 0.03 percent to close at 15,047.70 and the S&P 500 rose 6.50 points or 0.15 percent to end at 4,455.48. For the week, the Dow rose 0.6 percent, the NASDAQ added 0.1 percent and the S&P gained 0.5 percent.The lackluster performance on Wall Street came on uncertainty about the outlook for the markets following recent volatility.
