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Gilbert Garcia, San Antonio Express-News, 2 Dec. 2021 The motivation behind the law was clear from the beginning. 2021 Someone’s Christmas party followed, though details about that are less immediately clear.īill Goodykoontz, The Arizona Republic, 2 Dec. 2021 The rocks are effective, but Lamin Komma, head of coastal and marine environment at Gambia’s National Environment Agency, is clear about the project’s limitations. 2021 What isn’t as clear is the playoff fate of the runner-up.Įddie Timanus, USA TODAY, 5 Dec. 2021 Where all this new interim housing would go and how it would be funded isn’t exactly clear.īenjamin Oreskes, Los Angeles Times, 5 Dec. George Varga, San Diego Union-Tribune, 5 Dec. 2021 What is unmistakably clear is how unclear things are, at least for now. Recent Examples on the Web: Adjective And so just to be super clear: Are these new walkers going to make their way onto other Walking Dead shows?ĭalton Ross, EW.com, 6 Dec. The police ordered the crowd to clear the area. She cleared everything out of the closet.
#CLEAR ENVIRONMENT IN R RMLIST SKIN#
My skin cleared when I started using the cream. The water cleared after the mud had settled. When the smoke cleared, we could see that the building had been completely destroyed.
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The weather is cloudy now, but it's clearing gradually. I think I have a clear understanding of the problem. The instructions weren't very clear about when we were supposed to begin. “Changes will have to be made.” “Yes, that's clear.” It's not clear how much longer we'll have to wait.
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She has made it abundantly clear that she does not support us. I'm not completely happy with the plan, but I see no clear alternative. She's the clear favorite to win the election. I would be interested to infer ethnicity based on surname - another time.There are clear differences between the two candidates. Raw_data $ title ', nlevels( factor( raw_data $ surname)), ' unique surnames. Raw_data $ fare = mean( raw_data $ fare, na.rm = TRUE) Raw_data $ embarked = replace( raw_data $ embarked, which(is.na( raw_data $ embarked)), '$ ') Raw_data $ age = mean( raw_data $ age, na.rm = TRUE) Raw_data $ passenger_id = c( 1 :dim( raw_data)) Passenger_id is just an interger but with no statistical significance. Ggplot(aes( x =reorder( feature, - missing_pct), y = missing_pct)) + geom_bar( stat = 'identity ', fill = 'red ') + coord_flip() + theme_bw() Missing_values = gather( missing_values, key = 'feature ', value = 'missing_pct ') Missing_values = raw_data % >% summarise_all(funs(sum(is.na(. Lapply( raw_data, function( x) length(unique( x))) # Also it makes sense to have passenger_id as the first column We have 14 columns and target variable is 2ndĬolnames( raw_data) = 'passenger_id ' # Make target variable as the last one in the df Raw_data = read_excel( 'titanic.xlsx ', sheet = 'Titanic ') Library( 'reshape2 ') # data transformation Library( 'VIM ') # visualizing missing values Library( 'corrplot ') # correlation visualization Library( 'tidyverse ') # loads multiple packages Statistical Modeling, Algorithms, Machine Learning Predict the survival of passenger using the most influencing variables as predictorsĤ. What sorts of people were more likely to survive? Predict using passenger data (i.e., name, age, gender, socio-economic class, etc.). Thomas Andrews, her architect, died in the disaster. The Titanic was built by the Harland and Wolff shipyard in Belfast. The RMS Titanic was the largest ship afloat at the time it entered service and was the second of three Olympic-class ocean liners operated by the White Star Line.
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There were an estimated 2,224 passengers and crew aboard the ship, and more than 1,500 died, making it one of the deadliest commercial peacetime maritime disasters in modern history. The RMS Titanic was a British passenger liner that sank in the North Atlantic Ocean in the early morning hours of 15 April 1912, after it collided with an iceberg during its maiden voyage from Southampton to New York City.