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Numpy Reshape – How to reshape arrays and what does -1 mean?

How to reshape a numpy array? The numpy.reshape() function is used to reshape a numpy array without changing the data in the array. It is a very common practice to reshape arrays to make them compatible for further calculations. In this article, you will learn about the possible use cases of the numpy.reshape function.   …

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Pandas Sample – Randomly Sample Rows From Dataframe

Use the pandas.DataFrame.sample() method from pandas library to randomly select rows from a DataFrame Randomly selecting rows can be useful for inspecting the values of a DataFrame. In this article, you will learn about the different configurations of this method for randomly selecting rows from a DataFrame followed by a few practical tips for using …

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Pandas Describe

How to use Pandas Describe function? The pandas.describe function is used to get a descriptive statistics summary of a given dataframe. This includes mean, count, std deviation, percentiles, and min-max values of all the features. In this article, you will learn about different features of the describe function. We will also learn about the parameters …

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RegEx Replace values using Pandas

RegEx (Regular Expression) is a special sequence of characters used to form a search pattern using a specialized syntax While working on data manipulation, especially textual data, you need to manipulate specific string patterns. These may include retrieving hashtags from a tweet, extracting dates from a text, or removing website links. Pandas replace() function is …

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Pandas Histogram

Let’s understand how to create histogram in pandas and how it is useful. Histograms are very useful in statistical analysis. Histograms are generally used to represent the frequency distribution for a numeric array, split into small equal-sized bins. As we used pandas to work with tabular data, it’s important to know how to work with …

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Pandas Dropna – How to drop missing values?

In reality, majority of the datasets collected contain missing values due to manual errors, unavailability of information, etc. Although there are different ways for handling missing values, sometimes you have no other option but to drop those rows from the dataset. A common method for dropping rows and columns is using the pandas `dropna` function. …

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Pandas iloc – How to select rows using index in DataFrames?

#pandas iloc #python iloc Pandas iloc is a method for integer-based indexing, which is used for selecting specific rows and subsetting pandas DataFrames and Series. The command to use this method is pandas.DataFrame.iloc() The iloc method accepts only integer-value arguments. However, these arguments can be passed in different ways. In this article, you will understand …

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Machine Learning A-Z™: Hands-On Python & R In Data Science

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Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science