I have an excel file that has a date column, you are to fill the date column in this format: dd/mm/yyyy (as a string)

The issue I'm having now is that when I use pandas to read that excel file into a data frame, the values in the date column gets converted to an integer which is weird....has anybody experienced this before? I have no idea what's going on
 Yes, this is a common issue when reading Excel files into a pandas DataFrame. By default, pandas tries to convert date columns to its own datetime format, which can sometimes result in unexpected behavior.

To ensure that the date column is read as a string in the desired format, you can specify the `parse_dates` argument in the `read_excel()` function and set it to `False`. Here's an example:
```python
import pandas as pd

# Read the Excel file into a DataFrame
df = pd.read_excel('your_file.xlsx', parse_dates=False)

# Convert the date column to the desired format
df['date_column'] = df['date_column'].apply(lambda x: x.strftime('%d/%m/%Y') if isinstance(x, pd.Timestamp) else x)
```
In this example, replace `'your_file.xlsx'` with the path to your Excel file, and `'date_column'` with the name of the date column. The lambda function checks if the value is an instance of `pd.Timestamp`, and if so, converts it to the desired format using the `strftime()` method.

By setting `parse_dates=False`, you're telling pandas not to attempt to convert any
Yes, I have experienced this before. It appears that pandas is converting the date column to an integer because the dates are out of the default date range that pandas uses to store dates. To solve this, you can specify a custom date range by setting the pd.DatetimeIndex.min_date and pd.DatetimeIndex.max_date.