Before you begin, ensure your Excel data is well-organized. Each row should represent an individual record, and each column should have a header that will serve as the attribute name in DynamoDB. Save the Excel file in a CSV format, as this will simplify the parsing process in Python.

To interact with DynamoDB from Python, you'll need the `boto3` library, which is AWS's SDK for Python. Install it using pip:
```bash
pip install boto3 pandas
```
The `pandas` library will help you read and manipulate the CSV data.

Ensure that you have AWS credentials configured on your machine. You can do this by setting up the `~/.aws/credentials` file with your access key and secret key:
```ini
[default]
aws_access_key_id = YOUR_ACCESS_KEY
aws_secret_access_key = YOUR_SECRET_KEY
```
Alternatively, you can configure your credentials using the AWS CLI:
```bash
aws configure
```

Use Python to read the CSV file and convert it to a format suitable for DynamoDB:
```python
import pandas as pd

# Read the CSV file
data_frame = pd.read_csv('yourfile.csv')

# Convert DataFrame to a list of dictionaries
records = data_frame.to_dict(orient='records')
```

Ensure you have a DynamoDB table created in your AWS account. You can create a table using the AWS Management Console. Define your primary key (partition key, and optionally a sort key) based on the column(s) from your CSV file that uniquely identify each record.

Use Python to iterate over the records and insert them into the DynamoDB table:
```python
import boto3

# Initialize a session using Amazon DynamoDB
session = boto3.Session(region_name='us-west-2') # Update to your region
dynamodb = session.resource('dynamodb')

# Select your DynamoDB table
table = dynamodb.Table('YourDynamoDBTableName')

# Insert records into the table
with table.batch_writer() as batch:
for record in records:
batch.put_item(Item=record)
```

After the data transfer, verify that the data has been successfully inserted. You can use the AWS Management Console to scan the table and ensure all records are present. Optionally, write a small Python script to fetch and print records from the table to confirm:
```python
response = table.scan()
items = response['Items']
print(items)
```

By following these steps, you can efficiently move data from an Excel file to DynamoDB using Python without relying on third-party connectors or integrations.