Pandas dataframes are great for manipulating data. But, at times it might happen that you’d rather have the data as a list (or more precisely, a list of lists). In this tutorial, we’ll look at how to convert a pandas dataframe to a python list. How to covert a pandas dataframe to a list? There […]
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Generally, the data in each column represents a different feature of a pandas dataframe. It may be continuous, categorical, or something totally different like distinct texts. If you’re not sure about the nature of the values you’re dealing with, it might be a good exploratory step to know about the count of distinct values. In
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When working with pandas dataframes, it might be handy to know how to quickly replace values. In this tutorial, we’ll look at how to replace values in a pandas dataframe through some examples. How to replace values in a Pandas DataFrame? The pandas dataframe replace() function is used to replace values in a pandas dataframe.
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In this tutorial, we’ll look at how to convert a python list to a string. How to convert a python list to a string? You can use the string join() function in a list comprehension to easily create a string from the elements of the list. The following is the syntax: Here, we iterate through
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Filtering is one of the most common dataframe manipulations in pandas. When working with data in pandas dataframes, you’ll often encounter situations where you need to filter the dataframe to get a specific selection of rows based on your criteria which may even involve multiple conditions. In this tutorial, we’ll look at how to filter
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In this tutorial, we’ll cover how to get a random sample of columns of a pandas dataframe. The sample() function The pandas dataframe sample() function is generally used to sample rows from a dataframe. But you can also use it to sample columns by passing 1 or ‘columns’ to the axis parameter. The following is
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Pandas dataframes are great for handling two dimensional tabular data. It may happen that you require to randomly select a subset of rows from a dataframe. In this tutorial we’ll look at how to get a random sample of rows of a pandas dataframe. The sample() function The pandas dataframe sample() function can be used
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Excel files can be a great way of saving your tabular data particularly when you want to display it (and even perform some formatting to it) in a nice GUI like Microsoft Excel. In this tutorial, we’ll look at how to save a pandas dataframe to an excel .xlsx file. Note: The terms “excel file”
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Pandas dataframes are quite versatile when it comes to manipulating 2D tabular data in python. And often it can be quite useful to convert a numpy array to a pandas dataframe for manipulating or transforming data. In this tutorial, we’ll look at how to create a pandas dataframe from a numpy array. Using the pandas.DataFrame()
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NumPy arrays are the central data structure for applying the numerous useful operations defined in the NumPy library. Before you can start manipulating or transforming them, you’ll have to create them. In this tutorial, we’ll look at how some of the different ways to create numpy arrays. There are a number of different ways to
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