my code is # importing pandas for csv file operations import pandas as pd # filename to store the filename, change it to your filename fileName = 'survey.csv' # Creating a dataframe by opening the given file df = pd.read_csv(fileName) # converting the date string to datetime pd.to_datetime(df['Timestamp']) Question - Python code to drop the data values from your data set where the age is less than 1 or greater than 99. • Print the shape of your new data frame using the shape property. • Has the number of columns changed? • Has the number of rows changed? • Explain why each has or has not changed.
my code is # importing pandas for csv file operations import pandas as pd # filename to store the filename, change it to your filename fileName = 'survey.csv' # Creating a dataframe by opening the given file df = pd.read_csv(fileName) # converting the date string to datetime pd.to_datetime(df['Timestamp']) Question - Python code to drop the data values from your data set where the age is less than 1 or greater than 99. • Print the shape of your new data frame using the shape property. • Has the number of columns changed? • Has the number of rows changed? • Explain why each has or has not changed.
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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my code is
# importing pandas for csv file operations
import pandas as pd
# filename to store the filename, change it to your filename
fileName = 'survey.csv'
# Creating a dataframe by opening the given file
df = pd.read_csv(fileName)
# converting the date string to datetime
pd.to_datetime(df['Timestamp'])
Question - Python code to drop the data values from your data set where the age is less than 1 or greater than 99.
• Print the shape of your new data frame using the shape property.
• Has the number of columns changed?
• Has the number of rows changed?
• Explain why each has or has not changed.
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