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1. #Interquartile range how to#
2. #Interquartile range install#
3. #Interquartile range code#
4. #Interquartile range windows#

The range and interquartile range share the following similarity: Interquartile Range: Similarities & Differences

The range tells us the spread of the entire dataset while the interquartile range tells us the spread of the middle half of the dataset.

#Interquartile range how to#

I hope, you may find how to calculate the interquartile range in Python tutorial with step by step illustration of examples educational and helpful.In statistics, the range and interquartile range are two ways to measure the spread of values in a dataset. The Interquartile Range for all columns are as follows:Ĭool Tip: How to perform shapiro wilk test in python. The interquartile range for all the columns is shown below. We call this function using df.apply(calculateIQR). Our custom python function calculateIQR() accepts the data as input parameters which are columns of dataframe and returns the interquartile range for all columns. In the above example, we have created dataframe using the pandas package Dataframe() function. Print('\nThe Interquartile Range for all columns are as follows:\n',result) #define function to calculate interquartile range Then we calculate the interquartile range for the specific column i.e ‘maths’ in dataframe using the below python code. In this example, we create the data frame using the pandas package. Calculate IQR (Interquartile range) for dataframe column in python. #OutputĬool Tip: How to Calculate MAPE in python.

#Interquartile range code#

The output of the above code is shown below. Using () function, it calculates the interquartile range for the dataset. In the above code, we import the scipy package and then create an array. Iqr = stats.iqr(data, interpolation = 'midpoint') Let’s calculate the interquartile range for the data set using scipy library in the below code. we will use the same dataset defined for the above example.

#Interquartile range install#

pip install scipy Calculate Interquartile range of array in python.

#Interquartile range windows#

If you don’t have scipy library installed then use the below command on windows command prompt for scipy library installation. We will be using the Scipy library available in python, it provides () function to calculate interquartile range. Method 2:Use Scipy for Interquartile Range This is the spread of the middle 50% of values in the dataset.Ĭool Tip: How to Calculate MAPE in python. The Interquartile Range for the data is 17.5 for the above dataset.

The Interquartile Range for the data is: 17.5 Numpy.percentile() function accepts the dataset and percentiles of the quartiles as input parameters and returns the calculated quartiles.Īfter subtracting the first quartile from the third quartile we get the interquartile range for the dataset. In the above code, we import the NumPy package and creates an array for the data. Print('The Interquartile Range for the data is:',iqr) Let’s calculate the interquartile range for the data using the below python code. Calculate Interquartile range of array in python.ĭata = pip install numpyĬool Tip: How to Calculate SMAPE in python. If you don’t have numpy library installed then use the below command on the windows command prompt for NumPy library installation. We will be using the NumPy library available in python, it provides numpy.percentile() function to calculate interquartile range. 7 Conclusion Method 1:Interquartile Range using Numpy