Write a function that determines the number of missing entries for a specified column in the dataset. The function should return a string detailing the number of missing values. Function Specifications: Should take a pandas DataFrame and a column_name as input and return a string as output. The string should detial the number of missing entries in the column. Should be generalised to be able to work on ANY dataframe. ### START FUNCTION def total_missing(df,column_name): #code total_missing(df,'Age') Expected Outputs: total_missing(df,'Age') == "Age has 177 missing values" total_missing" (df,'Survived') == "Survived has 0 missing values"

Write a function that determines the number of missing entries for a specified column in the dataset. The function should return a string detailing the number of missing values. Function Specifications: Should take a pandas DataFrame and a column_name as input and return a string as output. The string should detial the number of missing entries in the column. Should be generalised to be able to work on ANY dataframe. ### START FUNCTION def total_missing(df,column_name): #code total_missing(df,'Age') Expected Outputs: total_missing(df,'Age') == "Age has 177 missing values" total_missing" (df,'Survived') == "Survived has 0 missing values"

C++ for Engineers and Scientists

4th Edition

ISBN:9781133187844

Author:Bronson, Gary J.

Publisher:Bronson, Gary J.

Chapter6: Modularity Using Functions

Section6.1: Function And Parameter Declarations

Problem 10E

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Question 2.2 Write a function createPassword()with no return value to randomly select 8 capital letters from the alphabet. The function receives the address of the first characters of the password string as parameter. Hint: Declare a characters string that contains all the capital letters of the alphabet and use the index values of the characters in the string for random selection of characters, e.g. char alpha [27] = “ABCDEFGHIJKLMNOPQRSTUVWXYZ”; char *pAlpha = alpha; Display the password from the main() function. Write a function replaceVowels() with no return value to replace all the vowels (A, E, I, O, U) that have been selected with a symbol from the list ($ % @ # &). That is, A must be replaced by $, E replaced by %, I must be replaced by @, O replaced by #, and U must be replaced by &. The function receives the address of the first characters of the password string as parameter. Display the password agin from the main() function.
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Now add a local variable in PrintInv() called Inventory. Have PrintInv() pass the structure to a new function called FindInv(), which will calculate and return the product of Price & Qty. In FindInv(), no new variable is needed. PrintInv() should give the same output as before, but now it uses FindInv() to find the product. ols0001 is the oldpart number, 0.80 is the oldpart price , 30 is the oldpart qty and 24.00 is the total inventory. Expected output: SMS0001 0.35 20 7.00 OLS0001 0.80 30 24.00 #include <stdlib.h>#include <stdio.h>#include <string.h>int main() { struct partitem { char number[10]; float price;};struct partitem part, oldpart;int oldpartqty; float oldpartprice;int qty = 20;part.price = 0.35;strcpy(part.number,"SMS0001");printf("price = %.2f\n",part.price);printf("name = %s \n", part.number);printf("quantity %d \n",qty );printf("enter oldpart\n");scanf("\n %s",oldpart.number);printf("\nold part number is…
Which of the following statements is true? A function: a. can have the same definition set as value setb. associates all different numbers in the definition set to a single number in the value setc.is a rule that for each element in a set connects it to just one element in another setd. is a rule that only converts natural numbers to whole numbersf. may not associate the same number in the value set with two different numbers in the definition set.h. must not associate one element in the definition set with several in the value seti. can very well associate several elements in the set of values with one in the definition set Mark all the answers that are correct.
Jupyter Notebook Fixed Income - Certicificate of Deposit (CD) - Compound Interest Schedule An interest-at-maturity CD earns interest at a compounding frequency, and pays principal plus all earned interest at maturity. Write a function, called CompoundInterestSchedule, that creates and returns a pandas DataFrame, where each row has: time (in years, an integer starting at 1), starting balance, interest earned, and ending balance, for an investment earning compoundedinterest. Use a for(or while) loop to create this table. The equation for theith year's ending balance is given by: Ei =Bi (1+r/f)f where: Ei is year i's ending balance Bi is year i's beginning balance (note: B1 is the amount of the initial investment (principal) r is the annual rate of interest (in decimal, e.g., 5% is .05) f is the number of times the interest rate compounds (times per year) The interest earned for a given year is Ei - Bi Note the term of the investment (in years) is not in the above equation; it is used…
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Write a function called daysOver that takes three arguments: a dictionary, a location (such as ‘Sydney’, ‘Adelaide’,etc) and a temperature and returns the number of days that were over the given temperature for the given location. For example, if we call the function using the line: total = daysOver(dictionaryData, ‘Adelaide’, 40) total will hold the number of days that Adelaide had a temperature greater than 40 celsius in the data. As a test, there were 54 days over 40 celsius in the data. Check that total is 54 for the example when you run your code. Use the daysOver function to print the number of days over 35 celsius for each of the following cities: 'Adelaide','Perth','Melbourne','Canberra','Sydney','Brisbane','Darwin' Which of the Australian cities has the most number of days over 35 celsius?
Using Pandas create a function that takes as input the data set (for example: sets) and returns the total number of rows in the data (as an integer)
Write a function which takes in a pandas dataframe and returns a modified dataframe that includes two new columns that contain information about the municipality and hashtag of the tweet. Function Specifications: Function should take a pandas dataframe as input. Extract the municipality from a tweet using the mun_dict dictonary given at the start of the notebook and insert the result into a new column named 'municipality' in the same dataframe. Use the entry np.nan when a municipality is not found. Extract a list of hashtags from a tweet into a new column named 'hashtags' in the same dataframe. Use the entry np.nan when no hashtags are found. Hint: you will need to mun_dict variable defined at the top of this notebook. ```
Python 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. I def calc_mean_mode(df, column_name): # your code here return calc_mean_mode(df,'Age') Expected Outputs: calc_mean_mode(df, 'Age') == 29.7 calc_mean_mode(df, 'Embarked') == ['S']
Write a function which splits the sentences in a dataframe's column into a list of the separate words. The created lists should be placed in a column named 'Split Tweets' in the original dataframe. This is also known as tokenization. Function Specifications: It should take a pandas dataframe as an input. The dataframe should contain a column, named 'Tweets'. The function should split the sentences in the 'Tweets' into a list of seperate words, and place the result into a new column named 'Split Tweets'. The resulting words must all be lowercase! The function should modify the input dataframe directly. The function should return the modified dataframe.