﻿ Pandas: Find average consumption of wine per person greater than a given number - w3resource

# Pandas: Find average consumption of wine per person greater than a given number

## Pandas Filter: Exercise-20 with Solution

Write a Pandas program to find average consumption of wine per person greater than 2 in world alcohol consumption dataset.

Test Data:

```   Year       WHO region                Country Beverage Types  Display Value
0  1986  Western Pacific               Viet Nam           Wine           0.00
1  1986         Americas                Uruguay          Other           0.50
2  1985           Africa           Cte d'Ivoire           Wine           1.62
3  1986         Americas               Colombia           Beer           4.27
4  1987         Americas  Saint Kitts and Nevis           Beer           1.98
```

Sample Solution:

Python Code :

``````import pandas as pd
# World alcohol consumption data
print("World alcohol consumption sample data:")
print("\nAverage consumption of wine per person greater than 2:")
print(w_a_con[(w_a_con['Beverage Types'] == 'Wine') & (w_a_con['Display Value'] > .2)].count())
``````

Sample Output:

```World alcohol consumption sample data:
Year       WHO region      ...      Beverage Types Display Value
0  1986  Western Pacific      ...                Wine          0.00
1  1986         Americas      ...               Other          0.50
2  1985           Africa      ...                Wine          1.62
3  1986         Americas      ...                Beer          4.27
4  1987         Americas      ...                Beer          1.98

[5 rows x 5 columns]

Average consumption of wine per person greater than 2:
Year              9
WHO region        9
Country           9
Beverage Types    9
Display Value     9
dtype: int64
```

Python Code Editor:

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## Python: Tips of the Day

Merging two dicts in Python 3.5+ with a single expression

Example:

```# How to merge two dictionaries
# in Python 3.5+

x = {'p': 1, 'q': 3}
y = {'q': 5, 'r': 8}

z = {**x, **y}

z
{'r': 4, 'p': 1, 'q': 3}

z = dict(x, **y)
print(z)
```

Output:

```{'p': 1, 'q': 5, 'r': 8}
```