Prompt Title: Convert string to Date

To convert the "releasedate" column to a date format in Python, we can use the to_datetime function from the pandas library. However, since the column contains dates in different formats, we need to specify the format for each date string using the format parameter.

Here's an example code snippet that you can use:

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import pandas as pd

# Read in your dataset
df = pd.read_csv('your_dataset.csv')

# Convert date strings to datetime format
df['releasedate'] = pd.to_datetime(df['releasedate'], 
                                    format='%Y-%m-%d', 
                                    errors='coerce')

df['releasedate'] = pd.to_datetime(df['releasedate'], 
                                    format='%d-%m-%y', 
                                    errors='coerce')

# Check the resulting dataframe
print(df.head())

In this code snippet, we first read in the dataset using the read_csv function from pandas. Then, we use the to_datetime function to convert the "releasedate" column to a datetime format. We specify two formats - %Y-%m-%d for the dates in the format 2016-01-06, and %d-%m-%y for the dates in the format 25-09-19. The errors='coerce' parameter is used to replace any invalid dates with NaT (Not a Time) values.

After converting the "releasedate" column, you can check the resulting dataframe using the head() function to make sure that the dates are now in datetime format.