### User Prompt

```
Task: Python script to merge CSVs
Input: Multiple CSVs, same columns
Constraints: Pandas only, <50 lines
Output: Single merged.csv
Verify: Run on test_data/
```

## General Code Structure
The current structure is an index.html and index.tsx with an es6 module that is automatically imported by the index.html.

## Sample Code for Merging CSVs
Here’s a simple Python script using Pandas to merge multiple CSV files:

```python
import pandas as pd
import glob

# glob to fetch all csv files
path = "test_data/"
all_files = glob.glob(path + "*.csv")

# list to hold dataframes
dfs = []

# loop through all files and read them into a dataframe
for file in all_files:
    df = pd.read_csv(file)
    dfs.append(df)

# merge all dataframes into a single dataframe
merged_df = pd.concat(dfs, ignore_index=True)

# write the merged dataframe to a new csv file
merged_df.to_csv("merged.csv", index=False)
print("CSV files have been merged successfully!")
```

## Explanation of the Code   
1. **Import Modules**: The `pandas` and `glob` modules are imported. `pandas` is used for data manipulation and analysis, while `glob` is used to retrieve files/pathnames matching a specified pattern.
2. **File Path**: Define the path where the CSV files are stored.
3. **Retrieve Files**: Use `glob.glob()` to get a list of all CSV files in the specified directory.
4. **Read and Append Dataframes**: Loop through the list of files, read each file into a DataFrame, and append it to a list.
5. **Merge Dataframes**: Use `pd.concat()` to combine the list of DataFrames into a single DataFrame.
6. **Save Merged CSV**: Write the combined DataFrame to a new CSV file.

## Testing the Script  
To confirm that the merging function works correctly, run the script in an environment where you have a folder named `test_data` containing multiple CSV files with the same columns. Check that the `merged.csv` file is created with all entries combined correctly.