Python | Basic summary statistics in Python: mean

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Summary statistics

Summary statistics are numerical values that provide a brief summary of the features of a dataset. In Python, you can use various libraries such as NumPy, Pandas, and SciPy to calculate summary statistics for your data.

Here are some common summary statistics that can be calculated in Python:

1. Mean: The arithmetic average of all the values in the dataset.

import numpy as np

data = [2, 4, 6, 8, 10]

mean = np.mean(data)

print(mean)

2. Median: The middle value in a dataset when it is arranged in ascending or descending order.

import numpy as np

data = [2, 4, 6, 8, 10]

median = np.median(data)

print(median)

3. Mode: The most frequently occurring value in the dataset.

from scipy import stats

data = [2, 4, 6, 6, 8, 8, 8, 10]

mode = stats.mode(data)

print(mode)

4. Range: The difference between the highest and lowest values in the dataset.

import numpy as np

data = [2, 4, 6, 8, 10]

range = np.max(data) - np.min(data)

print(range)

5. Standard deviation: A measure of the spread of the data from the mean.

import numpy as np

data = [2, 4, 6, 8, 10]

std_dev = np.std(data)

print(std_dev)

These are just a few examples of the summary statistics that can be calculated in Python. Depending on the specific needs of your analysis, you may need to calculate other summary statistics as well.