Blackboard Collat x2021 Springbbhosted.cuny.edu/webapps/assessment/take/launch.jsp?course_assessment_id=_1787700_1&course_id%3_1950256 1&content_id=_55349866 1&step3Dnull¥ Question Completion Status:Given a truth table below with the first two columns of truth values provided:b.f(p,q)1.4Which of the answers below contains the truth values for the third column when f(p,q) = ?Column 3Column 3Column 3truth values:Column 3truth values:Column 3truth values:truthtruthvalues:values:1 F1 T1 F1 F1 TNone of the other answersO 2 F2 T2 T2|Tprovided is correct.2 T3 T3 F3 T3 T3 F4 F4 F4 F4 T4 TSave All AnswersSaClick Save and Submit to save and subrzc Click SaveAll Answers to save all answers.a|曲pe here to searchT.F.F.2.3,

The truth table for the given question is as follows:

Answered: Given a truth table below with the…

Given a truth table below with the first two columns of truth values provided: f(p,q) T. T F .? 3. T 4. Which of the answers below contains the truth values for the third column when f(p,q) = ? %3D

Np Ms Office 365/Excel 2016 I Ntermed

1st Edition

ISBN:9781337508841

Author:Carey

Publisher:Carey

Chapter8: Working With Advanced Functions

Section: Chapter Questions

Problem 4.4CP

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Consider the below given iris data set. This dataset contains 3 classes of 15 instances each and each class refers to a type of iris plant. The dataset has two features: sepal length, sepal width. The third column is for species, which holds the value for these types of plants. A new plant is identified. You have to classify the Species class of new identified plant with the help of KNN algorithm. Note: Before applying KNN modify the given data by adding last two digits of your registration number. Such as if the last two digits of your registration number is 23 then first row in the given table will be 28.3and 26.3.
In cell H2, get the unique Area values using UNIQUE(). In column I, use COUNTIF() to get the count of each Area. Pass the data range from A2 to A45 as absolute addresses, and the filter criteria from H2 to H9. In column J, use COUNTIFS() to get the count of each area with more than 20 Swallow-tails. the first two arguments are the same as the previous step, then add a condition for column D to be greater than 20. Area Locality Skipper Swallowtail White-yellow Blue Brush-footed Area Count of Area Count of Area with 20 Swallowtails Indian Subcontinent Indian Subcontinent 307 94 99 458 482 Western Himalaya Western Himalaya 63 31 42 129 152 Western Himalaya Kangra Hills 25 23 37 56 87 Western Himalaya Shimla Hills 41 21 34 88 115 Western Himalaya Dehradun Valley 22 11 19 42 54 Western Himalaya Mussoorie Hills 54 23 32 88 126 Western Himalaya Mussoorie Town 14 10 13 44 65 Western Himalaya Kumaon Hills 52 26 37 109 147…
dataframe = pd.read_csv('https://raw.githubusercontent.com/Explore-AI/Public-Data/master/Data/regression_sprint/titanic_train_raw.csv') df = pd.read_csv('https://raw.githubusercontent.com/Explore-AI/Public-Data/master/Data/regression_sprint/titanic_test_raw.csv') Write a function that takes in as input a dataframe and a column name, and returns the mean for numerical columns and the mode for non-numerical columns. Function Specifications: The function should take two inputs: (df, column_name), where df is a pandas DataFrame, column_name is a str. If the column_name does not exist in df, raise a ValueError. Should return as output the mean if the specified column is numerical and return a list of the mode(s) otherwise. The mean should be rounded to 2 decimal places. If there is more than one mode for a given non-numerical column, the fuction should return a list of all modes. def calc_mean_mode(df, column_name): # your code here return calc_mean_mode(df,'Age') Expected Outputs:…
The InstantRide User Satisfaction team received a phone call from a user who might have left her wallet in the car. She indicated that the license plate of the car was starting with BB-883 but unfortunately, she could not remember the full license plate number. The team wants to get all travel information for the cars with the license plate starting with BB-883. You need to return all travel data from the TRAVELS table for the CAR_ID which has a plate number compared with SUBSTR and UPPER functions.
plz help me fix the following trigger problem is in picture CREATE OR REPLACE TRIGGER MEM_BALANCE AFTER UPDATE ON LATE_FEE FOR EACH ROW BEGIN UPDATE DETAILRENTAL SET LATE_FEE = CASE WHEN LATE_FEE = (DETAIL_DUEDATE – DETAIL_RETURNDATE) * DAILY_LATE_FEE WHEN LATE_FEE = (DETAIL_DUEDATE – DETAIL_RETURNDATE) * DAILY_LATE_FEE IS NULL THEN LATE_FEE := 0 WHEN UPDATED_LATE_FEE:= ORIGINAL_LATE_FEE – LATE_FEE WHEN UPDATED_LATE_FEE:= ORIGINAL_LATE_FEE – LATE_FEE IS NOT NULL THEN MEM_BALANCE:= TOTAL_BALNCE – UPDATED_LATE_FEE ELSE NULL END; the database im trying to put the trigger in CREATE TABLE MEMBERSHIP( MEM_NUM CHAR(3) CONSTRAINT MEMBER_MEM_NUM_PK PRIMARY KEY,MEM_FNAME VARCHAR(30) NOT NULL,MEM_LNAME VARCHAR(30) NOT NULL,MEM_STREET VARCHAR(15),MEM_CITY VARCHAR(10),MEM_STATE CHAR(2),MEM_ZIP CHAR(5),MEM_BALANCE NUMBER (2)); ALTER TABLE MEMBERSHIPMODIFY MEM_STREET VARCHAR(25);CREATE TABLE RENTAL( RENT_NUM CHAR(4) CONSTRAINT RENTAL_RENT_NUM_PK PRIMARY KEY,RENT_DATE DATE,MEM_NUM CHAR(3),CONSTRAINT…
convert UNF for 1NF to 2NF to 3NF, progressively. UNF:Order(OrderID, OrderDate, CustID, CustName, CustPhone, CCNum, CCExpDate, CCBank, BnkContName, BnkContPhone, CustEmail, OrderIP, SiteRefFrom, ShipStreet, ShipCity, ShipSt, ShipZip, OrderLineNum, ItemID, ItemName, ItemDesc, ItemQtyOrdered,ItemListPrice, ItemSalePrice, ItemQtyShip, ShipCharge, Tax, TotalDue)
V5. min jee wants to combine the sales data from each of the art fairs. switch to the combined sales worksheet and then update the worksheet as follows. in cell A5 enter a formula without using a function that references cell a5 in the Madison worksheet. copy the formula from cell a5 to the range a6:a8 without copying the formatting. in cell b5, enter a formula using the sum function, 3d references, grouped worksheets that totals the values from cell b:5 in the chicago: madison worksheets.
You are contracted to complete the data system for Citywide Taxi Company. Now, the information for each taxi is expanded to include: taxi id (such as CTC0001), the driver’s name, the maker of the Car (such as Ford), the model of the car (such as Escape), the Color of the Car (such as Black), the license number (such as HXT 4578), the number of passages the car served in the entire shift (integer type, this field will be left empty for this project). Your C++ program will (with array of class object): Define a class for the car with all members of variable mentioned above as private; Write all necessary class member functions to access those member variables (write or read); Read up to 50 records of data from the keyboard (provide a method to end the input before reaching 50 records) Save all records inputted from step 3 to a disk file called CTC.dat.
Consider the below given iris data set. This dataset contains 3 classes of 15 instances each and each class refers to a type of iris plant. The dataset has two features: sepal length, sepal width. The third column is for species, which holds the value for these types of plants. A new plant is identified. You have to classify the Species class of new identified plant with the help of KNN algorithm.KNN modify the given data by adding number 12 to special length and special width with everyone
You will use the wine for this task (dataset: sklearn.datasets.load_wine()), perform NN and NearestCentroid on the dataset to perform classification. Select different parameter values (i.e., parameter tuning) and discuss the influence. Finally, report result of comparisons. The dataset can be found here https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_wine.html
Write a python program based on the given dataset: https://docs.google.com/spreadsheets/d/1Gx0xyAahcCW0eTy6I_ge35Ekkig-TdcM/edit?usp=sharing&ouid=109069606642686211088&rtpof=true&sd=true Return the total aquaculture production by Region and Type/Environment. You must disregard the Philippines in the region column. Use groupby to group rows according to the Region and Type/Environment then apply the sum function to the Volume column to return total production per year. Sort the result base on Volume column.
1. You can manage risk in your orders by adding the TakeProfit/StopLoss attributes using fxcmpy. Group of answer choices True False 2. The following code retrieves and prints the candles data using the fxcmpy package. from fxcmpy import fxcmpy_candles_data_reader as cdr print(cdr.get_available_symbols()) Group of answer choices True False 3. Optimizers are a set of procedures defined in SciPy that either find the minimum value of a function or the root of an equation. Group of answer choices True False