Write codes in Jupyter notebook as required by the problems. Copy both code and output as screen grab or screen shot and paste them here. 1 Import the following files: uber_apr.csv, uber_may.csv, uber_jun.csv. Concatenate these files into a single file, uber. Print out the first 4 lines of the resulting DataFrame, Code and Output

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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Can you help me to find the phyton code and output
Write codes in Jupyter notebook as required by the problems. Copy both code and output as screen grab or screen shot and paste
them here.
1 Import the following files: uber_apr.csv, uber_may.csv, uber_jun.csv. Concatenate these files into a single file,
uber. Print out the first 4 lines of the resulting DataFrame,
Code and Output
2 Import tuberculosis.csv. Print the first five lines. Melt the DataFrame, keeping the country and year columns fixed.
Print the first five lines of the melted DataFrame,
Code and Output
Use the melted DataFrame in the previous problem. Create (and populate) a gender and an age column from the variable
column. Print the first five lines of the resulting DataFrame, Convert the age column to a numeric data type. Hint: use
ed to numeric, with the errors parameter equal to 'coerce'. Show evidence that this column has indeed been
transformed into a numeric.
Code and Output
3
Merge the files site.csv and visited.csv into a single ame. Use the column name of site and the column
site of visited. Make sure that the index labels are in order. Print the resulting DataFrame,
Code and Output
4
5 Import tips.csv. This dataset has a column named sex. Write a function named recode gender that has one
parameter (gender) and will recode Male to 0 and Female to 1, and will return np. nan if the value is neither Male nor
Female. Apply this function to the column sex of tips using apply (). Print the first five lines of the new dataframe.
Code and Output
Transcribed Image Text:Write codes in Jupyter notebook as required by the problems. Copy both code and output as screen grab or screen shot and paste them here. 1 Import the following files: uber_apr.csv, uber_may.csv, uber_jun.csv. Concatenate these files into a single file, uber. Print out the first 4 lines of the resulting DataFrame, Code and Output 2 Import tuberculosis.csv. Print the first five lines. Melt the DataFrame, keeping the country and year columns fixed. Print the first five lines of the melted DataFrame, Code and Output Use the melted DataFrame in the previous problem. Create (and populate) a gender and an age column from the variable column. Print the first five lines of the resulting DataFrame, Convert the age column to a numeric data type. Hint: use ed to numeric, with the errors parameter equal to 'coerce'. Show evidence that this column has indeed been transformed into a numeric. Code and Output 3 Merge the files site.csv and visited.csv into a single ame. Use the column name of site and the column site of visited. Make sure that the index labels are in order. Print the resulting DataFrame, Code and Output 4 5 Import tips.csv. This dataset has a column named sex. Write a function named recode gender that has one parameter (gender) and will recode Male to 0 and Female to 1, and will return np. nan if the value is neither Male nor Female. Apply this function to the column sex of tips using apply (). Print the first five lines of the new dataframe. Code and Output
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