Using the timestamp column as a reference, how does pandas categorize column values as Y if they fall between 100 and 160, and as N if they fall between 100 and 300?

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Assuming the timestamp column is named 'timestamp', you can use the following code to categorize column values:

import pandas as pd

# read data into a pandas dataframe
df = pd.read_csv('your_file.csv')

# convert timestamp column to datetime object
df['timestamp'] = pd.to_datetime(df['timestamp'])

# create a new column 'categorized' based on the timestamp values
df['categorized'] = df['timestamp'].apply(lambda x: 'Y' if x.minute >= 100 and x.minute <=160 else 'N' if x.minute > 160 and x.minute <= 300 else '-')

# print the updated dataframe 
print(df)

This code first converts the timestamp column to a datetime object using the pd.to_datetime() method. Then, it creates a new column 'categorized' using a lambda function that categorizes values as 'Y' or 'N' based on the minute value of the timestamp. Any values outside the specified range will be labeled with a '-' symbol.