﻿ Pandas Data Series: Calculate the frequency counts of each unique value of a given series - w3resource

# Pandas Data Series: Calculate the frequency counts of each unique value of a given series

## Pandas: Data Series Exercise-19 with Solution

Write a Pandas program to calculate the frequency counts of each unique value of a given series.

Sample Solution :

Python Code :

``````import pandas as pd
import numpy as np
num_series = pd.Series(np.take(list('0123456789'), np.random.randint(10, size=40)))
print("Original Series:")
print(num_series)
print("Frequency of each unique value of the said series.")
result = num_series.value_counts()
print(result)
``````

Sample Output:

```Original Series:
0     1
1     7
2     1
3     6
4     9
5     1
6     0
7     0
8     7
9     9
10    6
11    0
12    1
13    6
14    7
15    0
16    2
17    9
18    2
19    0
20    5
21    2
22    3
23    2
24    3
25    0
26    0
27    8
28    8
29    2
30    9
31    1
32    2
33    9
34    2
35    9
36    0
37    0
38    4
39    8
dtype: object
Frequency of each unique value of the said series.
0    9
2    7
9    6
1    5
6    3
8    3
7    3
3    2
4    1
5    1
dtype: int64
```

Python Code Editor:

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## Python: Tips of the Day

Function argument unpacking in Python.

Example:

```def tips_func(x, y, z):
print(x, y, z)

tuple_val = (2, 0, 2)
dict_val = {'x': 3, 'y': 2, 'z': 1}
tips_func(*tuple_val)
tips_func(**dict_val)
```

Output:

```2 0 2
3 2 1
```