prompter: Write me a python code with which i can merge two csv files that have the same name. They are in the same folder, but one version has "(2)" in the name.

assistant: Sure, here's an example Python code that uses the pandas library to merge two CSV files with the same name, where one file has "(2)" in its name:

```python
import pandas as pd
import os

# Set the file path and names
folder_path = "/path/to/folder"
file_name = "example.csv"
file_name2 = "example(2).csv"

# Read in the two CSV files
df1 = pd.read_csv(os.path.join(folder_path, file_name))
df2 = pd.read_csv(os.path.join(folder_path, file_name2))

# Merge the two dataframes based on a common column
merged_df = pd.merge(df1, df2, on="common_column")

# Write the merged dataframe to a new CSV file
merged_df.to_csv(os.path.join(folder_path, "merged_file.csv"), index=False)
```


Make sure to replace the "common_column" placeholder with the actual name of the column that is common to both CSV files and that you want to merge on. Also, replace the "folder_path" placeholder with the actual path to the folder where the CSV files are located. Finally, make sure that the file names in the code match the actual file names (including any parentheses or other characters in the file names).

assistant: Sure, here's an example Python code that you can use to merge two CSV files that have the same name, but one of them has "(2)" in the name:
``` import pandas as pd
import os

# Get the current working directory
cwd = os.getcwd()

# Set the file names of the two CSV files
file_name = "example.csv"
file_name_2 = "example(2).csv"

# Create the file paths for the two CSV files
file_path = os.path.join(cwd, file_name)
file_path_2 = os.path.join(cwd, file_name_2)

# Read the two CSV files into pandas DataFrames
df1 = pd.read_csv(file_path)
df2 = pd.read_csv(file_path_2)

# Merge the two DataFrames using the concat() function
merged_df = pd.concat([df1, df2], ignore_index=True)

# Save the merged DataFrame to a new CSV file
merged_file_name = "merged_example.csv"
merged_file_path = os.path.join(cwd, merged_file_name)
merged_df.to_csv(merged_file_path, index=False)
``` 
Here's how the code works:

1. We import the pandas library and the os library, which we will use to work with the file system.
2. We get the current working directory (cwd) using the os.getcwd() function.
3. We set the names of the two CSV files: file_name is the original file and file_name_2 is the file with "(2)" in the name.
4. We create the file paths for the two CSV files using the os.path.join() function.
5. We read the two CSV files into pandas DataFrames using the pd.read_csv() function.
6. We merge the two DataFrames using the pd.concat() function, which concatenates the rows of the two DataFrames together into a single DataFrame. The ignore_index=True argument ensures that the index of the merged DataFrame is reset to start from 0.
7. We save the merged DataFrame to a new CSV file using the to_csv() function.

Note that this code assumes that both CSV files have the same structure (i.e., the same columns in the same order). If the two CSV files have different structures, you may need to do additional processing to ensure that the merged DataFrame is in the format you need.

assistant: I can do that, but could you first specify what to do if the files don't have exactly the same columns:
- merge all columns and fill with empty values, or
- drop columns not common to both files, or
- stop with an error?