Use import sys. Use the german_credit_data.csv file to complete the following assignment. Create a file, german.py, that loads the .csv file and runs a regression predicting credit amount from age and duration, in that order. Add a constant using sm.add_constant(data). You will need to rename the column 'Credit amount' and should change it to 'Credit_amount'. Note: you will not need to upload the .csv to CodeGrade because I have pre-loaded it. Then, print the parameters and R-squared to 2 decimals using print(model.params.round(2)) print(model.rsquared.round(2))

Use import sys. Use the german_credit_data.csv file to complete the following assignment. Create a file, german.py, that loads the .csv file and runs a regression predicting credit amount from age and duration, in that order. Add a constant using sm.add_constant(data). You will need to rename the column 'Credit amount' and should change it to 'Credit_amount'. Note: you will not need to upload the .csv to CodeGrade because I have pre-loaded it. Then, print the parameters and R-squared to 2 decimals using print(model.params.round(2)) print(model.rsquared.round(2))

Np Ms Office 365/Excel 2016 I Ntermed

1st Edition

ISBN:9781337508841

Author:Carey

Publisher:Carey

Chapter5: Working With Excel Tables, Pivottables, And Pivotcharts

Section: Chapter Questions

Problem 11RA

See similar textbooks

Similar questions

I need help with Use the sacramento.csv file to complete the following assignment. Create a file, sacramento.py, that loads the .csv file and runs a logistic regression. The regression should predict whether or not a house has 1 or more than one bathroom based on beds, sqft, and price, in that order. Note: you will not need to upload the .csv to CodeGrade because I have pre-loaded it. You will need to create a new variable from baths, and it should make it such that those observations of 1 bath correspond to a value of 0, and those with more than 1 bath correspond to a 1. Make sure to add a constant using sm.add_constant(X) Your file should print the results in this way: print(mod.params.round(2)) print(mod.pvalues.round(2)) print('The smallest p-value is for sqft')
Use the sacramento.csv file to complete the following assignment. Create a file, sacramento.py, that loads the .csv file and runs a logistic regression. The regression should predict whether or not a house has 1 or more than one bathroom based on beds, sqft, and price, in that order. Note: you will not need to upload the .csv to CodeGrade because I have pre-loaded it. You will need to create a new variable from baths, and it should make it such that those observations of 1 bath correspond to a value of 0, and those with more than 1 bath correspond to a 1. Make sure to add a constant using sm.add_constant(X) Your file should print the results in this way: print(mod.params.round(2)) print(mod.pvalues.round(2)) print('The smallest p-value is for sqft')
Use import sys. Use the fastfood.csv file to complete the following assignment. Create a file, fastfood.py, that loads the .csv file and runs a regression predicting calories from total_fat, sat_fat, cholesterol, and sodium, in that order. Add a constant using sm.add_constant(data). Note: you will not need to upload the .csv to CodeGrade because I have pre-loaded it, but you will need to read in the data. Then, print the following to two decimals print(model.mse_total.round(2)) print(model.rsquared.round(2)) print(model.params.round(2)) print(model.pvalues.round(2))
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:…
Modify the accompanying credit risk data using IF functions to include new columns, classifying the checking and savings account balances as low if the balance is less than $250, medium if at least $250 but less than $2000, and high otherwise.
Using Sakila DB, create a function to get all the film titles for a given Actor. Example: getFilmTitle('firstname','lastname') Will return all the movies acted by the Actor. Put the screenshot of the implementation if you can.
you are required to read input file containing data of countries or region, to compute and display the data in decreasing order, and some statistics in an output file. Structure of input file: The first two lines of input files contains the region information, date of taken data, and heading of the records. Each line of the rest in the input file contains country name, confirmed and death total cases. COVID_19_data class: used to store records from input file. You should provide generic methods to compute average of confirmed cases, to sort list in descending order using selection sortii , and any additional method(s) to solve the problem. Tester Class: your main method should class two methods to read the data and to display the result as shown below. Your class should be user friendly and control any unchecked errors
i have insert a csv into a sql developer databse . there are many nulls like this INSERT INTO NAMES (YEAR, NAME, FREQUENCY, YEAR) VALUES (NULL,'',NULL,NULL);--Row 111,716INSERT INTO NAMES (YEAR, NAME, FREQUENCY, YEAR) VALUES (NULL,'',NULL,NULL);--Row 111,717INSERT INTO NAMES (YEAR, NAME, FREQUENCY, YEAR) VALUES (NULL,'',NULL,NULL);--Row 111,718INSERT INTO NAMES (YEAR, NAME, FREQUENCY, YEAR) VALUES (NULL,'',NULL,NULL);--Row 111,719INSERT INTO NAMES (YEAR, NAME, FREQUENCY, YEAR) VALUES (NULL,'',NULL,NULL);--Row 111,720INSERT INTO NAMES (YEAR, NAME, FREQUENCY, YEAR) VALUES (NULL,'',NULL,NULL);--Row 111,721INSERT INTO NAMES (YEAR, NAME, FREQUENCY, YEAR) VALUES (NULL,'',NULL,NULL);--Row 111,722INSERT INTO NAMES (YEAR, NAME, FREQUENCY, YEAR) VALUES (NULL,'',NULL,NULL);--Row 111,723INSERT INTO NAMES (YEAR, NAME, FREQUENCY, YEAR) VALUES (NULL,'',NULL,NULL);--Row 111,724INSERT INTO NAMES (YEAR, NAME, FREQUENCY, YEAR) VALUES (NULL,'',NULL,NULL);--Row 111,725INSERT INTO NAMES (YEAR, NAME,…
Consider the following code: import pandas as pd df = pd.DataFrame({'state': ['Ohio', 'Ohio', 'Ohio', 'Nevada'], 'year': [2000, 2001, 2002, 2001], 'pop': [1.5, 1.7, 3.6, 2.4]}) How can you sort the data? df.sort_values(by=['year']) Select one: True False
A data set has 4 columns--index, CUSTOMER_EMAIL, Net Revenue, and Year. For each year we need the following information: New Customer Revenue e.g., new customers not present in previous year only Lost Customers New Customers Total Customers Previous Year Total Customers Current Year Please implement it using python.
Can you explain the Dataset object in detail?
dataset in picture Use the given dataset to perform the following using python: Name of dataframe (your reg_no+your_name) Import the given data set Find out its header and information Calculate the mean, median and mode of covid_deaths, covid_recoveries, and covid_cases Find out the total of covid affected cases(all three cases) in all countries Find out the total of covid related deaths in all countries Countries covid_deaths covid_recoveries covid_cases Pakistan 10000 520000 55000 India 12000 120000 130000 Bangladesh 14000 123000 120000 Srilanka 19000 213000 45000 Bhutan 12000 212 44000 Nepal 1000 9000 12300 Australia 80000 560000 32100 Singapore 2000 130000 12345 England 100000 320000 89765 USA 100000 890000 87898