﻿ Pandas: Split the specified dataframe into groups and count unique values of 'value' column - w3resource # Pandas: Split the specified dataframe into groups and count unique values of 'value' column

## Pandas Grouping and Aggregating: Split-Apply-Combine Exercise-15 with Solution

Write a Pandas program to split the following dataframe into groups and count unique values of 'value' column.

Test Data:

```   id value
0   1     a
1   1     a
2   2     b
3   3  None
4   3     a
5   4     a
6   4  None
7   4     b
```

Sample Solution:

Python Code :

``````import pandas as pd
df = pd.DataFrame({
'id': [1, 1, 2, 3, 3, 4, 4, 4],
'value': ['a', 'a', 'b', None, 'a', 'a', None, 'b']
})
print("Original DataFrame:")
print(df)
print("Count unique values:")
print (df.groupby('value')['id'].nunique())
``````

Sample Output:

```Original DataFrame:
id value
0   1     a
1   1     a
2   2     b
3   3  None
4   3     a
5   4     a
6   4  None
7   4     b
Count unique values:
value
a    3
b    2
Name: id, dtype: int64
```

Python Code Editor:

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## Python: Tips of the Day

Negative Indexing:

In Python you can use negative indexing. While positive index starts with 0, negative index starts with -1.

```name="Welcome"
print(name)
print(name[-1])
print(name[0:3])
print(name[-1:-4:-1])

```

Output:

```W
e
Wel
emo```