Please use Jupyter Notebook Import gold.csv. Use the country name abbreviations as row index. Print the first three lines of the dataset.nd Output 1 Country NOC2 United Sta USA3 Soviet Uni URS4 United Kin GBR5 France FRA6 Germany GER7 Australia AUSITA8 Italy9 Hungary HUN10 Sweden SWE11 Netherland NED12 Romania ROU13 JapanJPN14 RussiaRUS15 Canada CAN16 East Germ GDR17 Poland POL18 FinlandFIN19 ChinaCHN20 West Gern FRG21 BrazilBRA22 Denmark DEN23 Belgium BEL24 Norway NOR25 Switzerlan SUI26 Bulgaria BULTotal208883849837840729346040034721215520619215432910312423414359147911947353

The answer is given below, the code implementation is in python language. Algorithm: Place the…

Answered: Please use Jupyter Notebook

Engineering

Computer Science

Please use Jupyter Notebook

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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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
Use the R data set “anscombe” to save a subset of all the columns of the data except x4 and y4
Create six TIME SERIES(USING pd.series function) and store in a Pandas data frame:a)The data frame must have an index that is a range of dates from 2016-01-01 until today.b)Each column contains one set of random numbers in a range 0 to 1 (each column will haveone random number for each date). number of columns = 6 number of rows = date range between today and 2016-01-01
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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))
The file london_weather.csv contains weather data for the years 1979 to 2020. The first five lines of this file are: date,cloud_cover,sunshine,global_radiation,max_temp,mean_temp,min_temp,precipitation,pressure,snow_depth19790101,2,7,52,2.3,-4.1,-7.5,0.4,101900,919790102,6,1.7,27,1.6,-2.6,-7.5,0,102530,819790103,5,0,13,1.3,-2.8,-7.2,0,102050,419790104,8,0,13,-0.3,-2.6,-6.5,0,100840,2 Note, in particular, that the dates are given as eight-digit integers in the format YYYYMMDD. There appears to be some inconsistencies in this data, as there are rows for which the column max_temp contains an entry that is smaller than the corresponding entry in min_temp. Write a Python function wrong_temperature(year) that returns the number of days in a given year for which the column max_temp contains an entry that is smaller than the corresponding entry in the column min_temp.
Use Python Code Your task is : Visualization of confirmed cases of COVID-19 by country . (Use pandas to read the data table csv. Example df = pd.read_csv('COVID19.csv' ) then make a visualization using that csv table) Province/State Country Lat Long ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## 2/1/2020 2/2/2020 2/3/2020 2/4/2020 2/5/2020 2/6/2020 2/7/2020 2/8/2020 2/9/2020 ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## 3/1/2020 3/2/2020 3/3/2020 3/4/2020 3/5/2020 3/6/2020 3/7/2020 3/8/2020 3/9/2020 ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## 4/1/2020 4/2/2020 4/3/2020 4/4/2020 4/5/2020 4/6/2020 4/7/2020 Afghanistan 33 65 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0…
1. Read a give “data.csv” file, analyze the data, write the analysis result to“report.txt” file :in the report.txt file: include information of:1). How many rows in this dataset, for example: “This dataset has 10 rows”2). How many columns in this dataset, for example:”This dataset has 3 col-umns.”3). What are the name for the columns, print the all the column names, forexample, “The 3 columns are: name,age,gpa”4). How many numeric column(s), for example, “ This dataset has 2 numericcolumns, they are age, and gpa”5). The mean (avarage) of each column, for example, “The means are:mean1, mean2” python
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Create the following sample data file in SPSS and calculate the BMI(Body Mass Index) and show it in the next column as shown below: The formula to calculate BMI is BMI= Weight / ( Height * Height) * 703
Open the link below and select 2 CSV datasets and 2 xlsx datasets from it. Or you can select any data sets from the web. https://data.europe.eu/euodp/en/data/dataset?sort=views total+desc Please use the R programming software to answer the following Questions: 1- Describe the selected table and its columns in words, list down the data types of all columns. 2- Apply (sum, average, count, max, and min) function where applicable, justfy why you applied that function and write the results. 3- Draw pie, bar, boxplot, and histogram where possible in order to draw the specific type of chart the data appropriation is important. Some charts will not be feasible for some data. So you need to find out the appropriate data set and its properties that are suitable for a specific type of chart.
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