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Python Programming for Data Science   Introduction Python has become one of the most popular programming languages in the field of Data Science due to its simplicity, versatility, and the availability of powerful libraries and tools. In this article, we will explore some of the essential tools and libraries for Python programming in Data Science. These tools and libraries are crucial for data analysis, machine learning, and visualization, and are widely used in industry and academia. Join Best Data Science Training in Gurgaon .   NumPy NumPy is a powerful Python library for numerical computing. It provides support for large, multi-dimensional arrays and matrices, along with a variety of mathematical functions to operate on them. NumPy is essential for data analysis and is often used in conjunction with other Python libraries such as Pandas and Matplotlib.   Pandas Pandas is another essential Python library for data analysis. It provides data structures for efficient h

Techniques and Tools for Understanding Data Introduction Exploratory Data Analysis (EDA) is an important step in the data analysis process that involves examining and understanding the data before applying any formal statistical methods. EDA helps in identifying patterns, relationships, and anomalies in the data and provides insights into the quality and suitability of the data for further analysis. In this article, we will discuss the various techniques and tools used in EDA to help understand data.  Data science course in gurgaon with placement .   Descriptive Statistics Descriptive statistics is a set of techniques used to summarize and describe the data in a meaningful way. Some of the common descriptive statistics include measures of central tendency (mean, median, mode), measures of variability (range, standard deviation, variance), and measures of shape (skewness, kurtosis). These statistics provide an initial understanding of the data and help in identifying outliers an