Download any Dataset, then write a python code to read the downloaded dataset of your choice (April be CSV file) and print all features i.e. columns of the dataset. Determine the descriptive statistics i.e. Mean Median, Maximum, Minimum ,Range, Count, Variance, Standard Deviation etc. of the numeric features like age, marks, income etc., which April be present in the dataset.

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Sure thing! Let's break down the task into steps.

Firstly, we need to download a dataset. For simplicity, I'll use a common dataset available in many examples: the Iris dataset. This dataset contains information about iris flowers, and it's available in a CSV format.

```python
import pandas as pd

# Download the Iris dataset from a URL
url = "https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data"
column_names = ["sepal_length", "sepal_width", "petal_length", "petal_width", "class"]
iris_data = pd.read_csv(url, names=column_names)

# Print the columns/features of the dataset
print("Features/Columns of the Dataset:")
print(iris_data.columns)
```

Next, let's calculate the descriptive statistics for numeric features like sepal length, sepal width, petal length, and petal width.

```python
# Print descriptive statistics for numeric features
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Degree : PG DIPLOMA PROGRAMMES
Course Name : POST GRADUATE DIPLOMA IN COMPUTER APPLICATIONS
Course Code : PGDCA_NEW
Subject Name : C and PYTHON Lab
Subject Code : MCSL 205
Year : 2023