Consider we have loaded our data frame, named NBA, using the data in the file below. Write a single statement that can find a numberof unique playing positions?NameТeamNumberPositionAgeHeightAvery Bradley Boston CelticsPG256-2Jae Crowder Boston Celtics99SF256-6John Holland Boston Celtics30SG276-5RJ. HunterBoston Celtics28SG226-5Jonas Jerebko Boston Celtics8PF296-10Amir Johnson Boston Celtics90PF296-9Jordan Mickey Boston Celtics55PF216-8Kelly Olynyk Boston CelticsTerry Rozier Boston Celtics41257-012PG226-2Marcus Smart Boston Celtics36PG226-4Jared Sullinger Boston Celtics7246-9Isaiah Thomas Boston Celtics4PG275-9Evan TumerBoston Celtics11SG276-7O a. NBA [Position].unique ()O b. NBA.position.unique ()O . NBA[ 'Position'].unique ()O d. NBA. Position.notRepeat()

Pandas Index.unique() function return unique values in the index. Uniques are returned in order of…

Consider we have loaded our data frame, named NBA, using the data in the file below. Write a single statement that can find a number of unique playing positions? Name Team Number Position Age Height 6-2 Avery Bradley Boston Celtics PG 25 Jae Crowder Boston Celtics 99 SF 25 6-6 John Holland Boston Celtics 30 SG 27 6-5 RJ. Hunter Boston Celtics 28 SG 22 6-5 Jonas Jerebko Boston Celtics PF 29 6-10 Amir Johnson Boston Celtics 90 PF 29 6-9 Jordan Mickey Boston Celtics Kelly Olynyk Boston Celtics Terry Rozier Boston Celtics 55 PF 21 6-8 41 25 7-0 12 PG 22 6-2 Marcus Smart Boston Celtics 36 PG 6-4 Jared Sullinger Boston Celtics 7 24 6-9 Isaiah Thomas Boston Celtics 4 PG 27 5-9 Evan Turner Boston Celtics SG 27 6-7 11 O a. NBA (Position].unique () O b. NBA.position.unique () O C. NBA[ 'Position'].unique () O d. NBA.Position.notRepeat()

Consider we have loaded our data frame, named NBA, using the data in the file below. Write a single statement that can find a number of unique playing positions? Name Team Number Position Age Height 6-2 Avery Bradley Boston Celtics PG 25 Jae Crowder Boston Celtics 99 SF 25 6-6 John Holland Boston Celtics 30 SG 27 6-5 RJ. Hunter Boston Celtics 28 SG 22 6-5 Jonas Jerebko Boston Celtics PF 29 6-10 Amir Johnson Boston Celtics 90 PF 29 6-9 Jordan Mickey Boston Celtics Kelly Olynyk Boston Celtics Terry Rozier Boston Celtics 55 PF 21 6-8 41 25 7-0 12 PG 22 6-2 Marcus Smart Boston Celtics 36 PG 6-4 Jared Sullinger Boston Celtics 7 24 6-9 Isaiah Thomas Boston Celtics 4 PG 27 5-9 Evan Turner Boston Celtics SG 27 6-7 11 O a. NBA (Position].unique () O b. NBA.position.unique () O C. NBA[ 'Position'].unique () O d. NBA.Position.notRepeat()

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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Consider the following a file (movies.txt) with the following list of movies (comma separated list). SNO, Name, NoOfPeopleLiked 1, The Shawshank Redemption, 77 2, The Godfather, 20 3, Into The Wild, 35 4, The Dark Knight, 55 5, 12 Angry Men, 44 6, Schindler's List, 33 7, The Lord of the Rings: The Return of the King, 25 8, Pulp Fiction, 23 9, The Good, the Bad and the Ugly, 32 10, The Lord of the Rings: The Fellowship of the Ring, 56
Please Assist me to complete the Python Code: Data frames can be subset by a chosen value using ==. Ex: df[df.x == 5] gives all the rows in the data frame df for which the column x has a value of 5. Write a program that performs the following tasks: Load the file mtcars.csv into a data frame called df Create a new data frame df_cyl by subsetting the data frame based on a user defined value for the column cyl. Print the shape of the new data frame.mtcars.csv should not be necessary to answer this question. Please advise on the commands for subsetting a new data frame and for printing the shape of the new data frame. Thank You! Please try Completing the Program Below: import pandas as pd cylinders = int(input()) df = # read in the csv file mtcars.csv df_cyl = # create a new dataframe with only the rows where cyl = cylinders print(# print the shape of the new data frame)
Given the following json file, create a Python program that reads the file and outputs an XML file that groups car data appropriately. { "cars": [ { "make": "Honda", "model": "Accord", "color": "White", "engine": "I4", "transmission": "Automatic", "price": 22756.0 }, { "make": "Chevrolet", "model": "Bolt EV", "color": "Gray", "engine": "Not Specified", "transmission": "Automatic", "price": 39551.0 }, { "make": "Dodge", "model": "Challenger", "color": "Gray", "engine": "V6", "transmission": "Automatic", "price": 32216.0 } ]}
In The Readline Technique, on page 179, you learned how to read somefiles from the Time Series Data Library. In particular, you learned aboutthe Hopedale data set, which describes the number of colored fox fur peltsproduced from 1834 to 1842. This file contains one value per year perline.a. Write an outline in English of the algorithm you would use to readthe values from this data set to compute the average number of peltsproduced per year.b. Translate your algorithm into Python by writing a function namedhopedale_average that takes a filename as a parameter and returns theaverage number of pelts produced per year.
The acclaimed _NumPy_ library, that `Simpy` is inspired by, allows you to use the subscription operator not just to select individual items, but also to filter with a mask. It adds a second usage to the operator, just like you have had two uses of many of the operators above, such as adding two `Simpy`s or a `Simpy` and a `float`. The big idea of the second usage of subscription notation is that if instead of giving an `int` inside the subscription brackets you give a `list[bool]`, the expression will return a new `Simpy` object containing only the _masked_, or filtered, `values`. For example: ~~~python a = Simpy([1.0, 2.0, 3.0, 4.0, 2.0, 1.0]) mask = a > 2.0 print(mask) # Output: [False, False, True, True, False, False] b = a[mask] print(b) # Output: Simpy([3.0, 4.0]) ~~~ The above example did not need to establish a separate variable named `mask`, it only did so to make it obvious what the `mask` values were. More conventionally, the above example would be written in a…
Javascript: Using the data set as a pre-defined variable in your program, write code that uses the dataset to print the FIRST NAMES ONLY of people who have BOTH above average English grades AND below average age from the dataset. var dataSet = [ { "name":"Maura Glass", "age":60, "math":97, "english":63, "yearsOfEducation":4 }, { "name":"James Gates", "age":55, "math":72, "english":96, "yearsOfEducation":10 }, { "name":"Mills Morris", "age":26, "math":83, "english":77, "yearsOfEducation":10 }, { "name":"Deena Morton", "age":57, "math":63, "english":63, "yearsOfEducation":10 }, { "name":"Edith Roth", "age":38, "math":79, "english":94, "yearsOfEducation":10 }, { "name":"Marva Morse", "age":31, "math":93, "english":78, "yearsOfEducation":9 }, { "name":"Etta Potts", "age":48, "math":57, "english":93, "yearsOfEducation":7 }, { "name":"Tate Moss", "age":22, "math":83, "english":64, "yearsOfEducation":8 }, { "name":"Sanders Burris", "age":27, "math":65, "english":66, "yearsOfEducation":5…
you will be identifying which organisms are the tastiest. The tastiest organisms are the ones that appear the most times as a food source. For example if aquatic.txt was the input file, file_list will be: ["Bird,Prawn,Mussels,Crab,Limpets,Whelk\n", "Crab,Mussels,Limpets\n", "Fish,Prawn\n", "Limpets,Seaweed\n", "Lobster,Crab,Mussels,Limpets,Whelk\n", "Mussels,Phytoplankton,Zooplankton\n", "Prawn,Zooplankton\n", "Whelk,Limpets,Mussels\n", "Zooplankton,Phytoplankton"] Limpets and mussels appear the most times as a food source, making them the tastiest organisms. Here is a sample output using aquatic.txt: Enter the food web file name: aquatic.txt Predators and Prey: Bird eats Crab, Limpets, Mussels, Prawn, and Whelk Crab eats Limpets and Mussels Fish eats Prawn Limpets eats Seaweed Lobster eats Crab, Limpets, Mussels, and Whelk Mussels eats Phytoplankton and Zooplankton Prawn eats Zooplankton Whelk eats Limpets and Mussels Zooplankton eats Phytoplankton Apex Predators:…
In python >>> build_csv_string([["Sam", "Lab 01", 5.4]]) 'name,assignment,grade\nSam,Lab 01,5.4' >>> build_csv_string([["Sam", "Lab 01", 5.4], ["Zoe"]]) 'name,assignment,grade\nSam,Lab 01,5.4\nZoe,N/A,0' >>> build_csv_string([["Sam", "Lab 01", 5.4], ["Zoe"], ["Amanda", "Quiz 04", 100]]) 'name,assignment,grade\nSam,Lab 01,5.4\nZoe,N/A,0\nAmanda,Quiz 04,100'
In this project, you will develop algorithms that find road routes through the bridges to travel between islands. The input is a text file containing data about the given map. Each file begins with the number of rows and columns in the map considered as maximum latitudes and maximum longitudes respectively on the map. The character "X" in the file represents the water that means if a cell contains "X" then the traveler is not allowed to occupy that cell as this car is not drivable on water. The character "0" in the file represents the road connected island. That means if a cell contains "0" then the traveler is allowed to occupy that cell as this car can drive on roads. The traveler starts at the island located at latitude = 0 and longitude = 0 (i.e., (0,0)) in the upper left corner, and the goal is to drive to the island located at (MaxLattitude-1, MaxLongitudes-1) in the lower right corner. A legal move from an island is to move left, right, up, or down to an immediately adjacent…
In this project, you will develop algorithms that find road routes through the bridges to travel between islands. The input is a text file containing data about the given map. Each file begins with the number of rows and columns in the map considered as maximum latitudes and maximum longitudes respectively on the map. The character "X" in the file represents the water that means if a cell contains "X" then the traveler is not allowed to occupy that cell as this car is not drivable on water. The character "0" in the file represents the road connected island. That means if a cell contains "0" then the traveler is allowed to occupy that cell as this car can drive on roads. The traveler starts at the island located at latitude = 0 and longitude = 0 (i.e., (0,0)) in the upper left corner, and the goal is to drive to the island located at (MaxLattitude-1, MaxLongitudes-1) in the lower right corner. A legal move from an island is to move left, right, up, or down to an immediately adjacent…
"""Q2: Using numpy and pyplot, make an overlapping histogram that shows the score distribution vs. count of R-Rated movies and PG-13 ones.Describe your plot. Save your plot in a variable called plt2, and your dataframes in variables called df_R and df_PG13""" import matplotlib.pyplot as plt2 # your code here plt2.show() """to test Q2: assert_frame_equal(df_R, sol.df_R)assert_frame_equal(df_PG13, sol.df_PG13)np.testing.assert_array_equal(plt2, sol.plt2)print("Success!")
Write a python program based on the given dataset link: https://docs.google.com/spreadsheets/d/1Gx0xyAahcCW0eTy6I_ge35Ekkig-TdcM/edit?usp=sharing&ouid=109069606642686211088&rtpof=true&sd=true Return the total aquaculture production volume of the Philippines per year and Type/Environment. Filter rows based on the Philippines region only, use groupby to group rows according to the year and Type/Environment then apply the sum function to the Volume column to return total production per year.