What is the use of series.describe method in Pandas?

PandasServer Side ProgrammingProgramming

The describe() method in the pandas.series is used to generate the statistical description of a series object. This method analyzes the description of both numerical and objective series.

As a result, the describe() method returns a summarized statistics of the series. It varies depending on the type of input series object.

For numerical series, the describe() method analyzes basic statistics like count, mean, std, min, max, and quantile (25%, 50%, and 75%). The 50% quantile is the same as the median.

If the series object has object type data, the describe() method analyzes basic statistics like count, unique, top, and freq.

Example 1

# importing required packages
import pandas as pd

# creating pandas Series object
series = pd.Series([9,2,3,5,8,9,1,4,6])
print(series)

# apply describe method
print("output",series.describe())

Explanation

Initially, we have created a pandas Series with a python list of integer values. And analyzed the statistics of the series object by using describe() method.

Output

0 9
1 2
2 3
3 5
4 8
5 9
6 1
7 4
8 6
dtype: int64

Output count  9.000000
mean 5.222222
std  2.990726
min  1.000000
25%  3.000000
50%  5.000000
75%  8.000000
max  9.000000
dtype: float64

We calculated the basic statistics of the numerical series object, the results are displayed in the above output block. The count represents the number of elements of the given series object. In the same way, we analyzed the mean, minimum, maximum, standard deviation, and so on.

Example 2

# importing required packages
import pandas as pd

# creating pandas Series object
series = pd.Series(['A', 'B', 'E', 'C', 'A', 'D', 'D', 'E', 'F', 'C', 'B', 'A'])
print(series)

# apply describe method
print("Output: ">"",series.describe())

Explanation

In this following example, we calculated the statistics on an objective type pandas series. For that, we created a series object using a list of strings.

Output

0  A
1  B
2  E
3  C
4  A
5  D
6  D
7  E
8  F
9  C
10 B
11 A
dtype: object

Output count 12
unique 6
top    A
freq   3
dtype: object

We got the count of series elements, the total number of unique values, the top (topmost frequent) element, and the frequency of the top value.

raja
Updated on 09-Mar-2022 09:27:20

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