Parse Date Formats Practice Problem

This data science coding problem helps you practice Data Type Conversion & Validation, parse date formats, and implementation skills. Read the problem statement, write your solution, and strengthen your understanding of Data Type Conversion & Validation.

• Problem ID: 40
• Problem key: 40-parse-date-formats
• URL: https://datacrack.app/solve/40-parse-date-formats
• Difficulty: easy
• Topic: Data Type Conversion & Validation
• Module: Data Cleaning

Problem Statement

# Parse Date Formats

### 🎯 Goal
Parse date strings from various formats into a standardized ISO format (`YYYY-MM-DD`).

### 💻 Task
Implement `parse_dates(data, column)` that:
1. Converts the input dictionary to a DataFrame
2. Parses the specified column using `pd.to_datetime` (auto-detecting the format)
3. Converts the parsed dates to ISO format strings (`YYYY-MM-DD`)
4. Returns the resulting DataFrame

---

### 📥 Input
- `data`: A dictionary where keys are column names and values are lists of date strings
- `column`: The name of the column containing date strings

### 📤 Output
- A pandas DataFrame with the date column converted to ISO format strings (`YYYY-MM-DD`)

---

### 🧩 Starter Code

```python
import pandas as pd
import numpy as np

def parse_dates(data, column):
    """
    Parse date strings from various formats into ISO format.

    Args:
        data (dict): Input data as dictionary with date strings
        column (str): Name of the column containing dates

    Returns:
        pd.DataFrame: DataFrame with dates as ISO format strings
    """
    # TODO: Convert the input dictionary to a DataFrame
    # TODO: Use pd.to_datetime to parse the date column
    # TODO: Convert parsed dates to ISO format strings (YYYY-MM-DD)
    # TODO: Return the resulting DataFrame
    pass
```

---

### 💡 Examples

**Example 1:** ISO format input (already standard)
```python
data = {"date": ["2024-01-15", "2024-03-20", "2024-06-10"]}
parse_dates(data, "date")
```
```
         date
0  2024-01-15
1  2024-03-20
2  2024-06-10
```

**Example 2:** European day/month/year format
```python
data = {"date": ["15/01/2024", "20/03/2024", "10/06/2024"]}
parse_dates(data, "date")
```
```
         date
0  2024-01-15
1  2024-03-20
2  2024-06-10
```

**Example 3:** Month name format
```python
data = {"date": ["Jan 15, 2024", "Mar 20, 2024", "Jun 10, 2024"]}
parse_dates(data, "date")
```
```
         date
0  2024-01-15
1  2024-03-20
2  2024-06-10
```

Starter Code

import pandas as pd
import numpy as np

def parse_dates(data, column):
    """
    Parse date strings from various formats into ISO format.

    Args:
        data (dict): Input data as dictionary with date strings
        column (str): Name of the column containing dates

    Returns:
        pd.DataFrame: DataFrame with dates as ISO format strings
    """
    # TODO: Convert the input dictionary to a DataFrame
    # TODO: Use pd.to_datetime to parse the date column
    # TODO: Convert parsed dates to ISO format strings (YYYY-MM-DD)
    # TODO: Return the resulting DataFrame
    pass