This is programmed in MATLAB. Please provide the code for PART F PART G. This should be organized with a PIPELINE/WORKFLOW style

f) The CSV file "is.canada.csv" identifies with a binary variable (0/1) if the home_dest variable mentions any Canadian city (either as home or destination). Join this information to the main data set, such that you add an 11th variable to the titanic table, named country, that will take either the value "Canada" if the the passenger's home_dest variable is related to Canada, or "other" else. g) Plot the survival bar chart by sex and class (using plot survival()) only for the passengers that have been identified being related to Canada (as per their home_dest value). 1 home_dest 2 St Louis, MO 3 Montreal, PQ/ Chesterville, ON 4 New York, NY 5 Hudson, NY 6 Belfast, NI 7 Bayside, Queens, NY 8 Montevideo, Uruguay 9 Paris, France 10 Hessle, Yorks 11 Montreal, PQ 12 Winnipeg, MN 13 San Francisco, CA 14 Dowagiac, MI 15 Stockholm, Sweden / Washington, DC 16 Trenton, NJ 17 Glen Ridge, NJ 18 Youngstown, OH 19 Birkdale, England Cleveland, Ohio 20 London / Winnipeg, MB 21 Cooperstown, NY country other Canada other other other other other other other Canada Canada other other other other other other other Canada other 353 Union Hill, NJ other 354 London New York, NY other 355 Austria Niagara Falls, NY other 356 Ballydehob, Co Cork, Ireland New York, N other 357 West Haven, CT other 358 Austria-Hungary other 359 Tofta, Sweden Joliet, IL other 360 Karberg, Sweden Jerome Junction, AZ other 361 Effington Rut, SD other 362 Illinois, USA other 363 Aughnacliff, Co Longford, Ireland New Yo other 364 Italy Philadelphia, PA other 365 Bridgwater, Somerset, England other 366 Rotherfield, Sussex, England Essex Co, M. other 367 Co Clare, Ireland Washington, DC other 368 Strood, Kent, England Detroit, MI other 369 Wiltshire, England Niagara Falls, NY other 370 Dorking, Surrey, England other 371 Foresvik, Norway Portland, ND other 372 Waukegan, Chicago, IL other 373 Myren, Sweden New York, NY other f) The CSV file "is.canada.csv" identifies with a binary variable (0/1) if the home_dest variable mentions any Canadian city (either as home or destination). Join this information to the main data set, such that you add an 11th variable to the titanic table, named country, that will take either the value "Canada" if the the passenger's home_dest variable is related to Canada, or "other" else. g) Plot the survival bar chart by sex and class (using plot survival()) only for the passengers that have been identified being related to Canada (as per their home_dest value). 1 home_dest 2 St Louis, MO 3 Montreal, PQ/ Chesterville, ON 4 New York, NY 5 Hudson, NY 6 Belfast, NI 7 Bayside, Queens, NY 8 Montevideo, Uruguay 9 Paris, France 10 Hessle, Yorks 11 Montreal, PQ 12 Winnipeg, MN 13 San Francisco, CA 14 Dowagiac, MI 15 Stockholm, Sweden / Washington, DC 16 Trenton, NJ 17 Glen Ridge, NJ 18 Youngstown, OH 19 Birkdale, England Cleveland, Ohio 20 London / Winnipeg, MB 21 Cooperstown, NY country other Canada other other other other other other other Canada Canada other other other other other other other Canada other 353 Union Hill, NJ other 354 London New York, NY other 355 Austria Niagara Falls, NY other 356 Ballydehob, Co Cork, Ireland New York, N other 357 West Haven, CT other 358 Austria-Hungary other 359 Tofta, Sweden Joliet, IL other 360 Karberg, Sweden Jerome Junction, AZ other 361 Effington Rut, SD other 362 Illinois, USA other 363 Aughnacliff, Co Longford, Ireland New Yo other 364 Italy Philadelphia, PA other 365 Bridgwater, Somerset, England other 366 Rotherfield, Sussex, England Essex Co, M. other 367 Co Clare, Ireland Washington, DC other 368 Strood, Kent, England Detroit, MI other 369 Wiltshire, England Niagara Falls, NY other 370 Dorking, Surrey, England other 371 Foresvik, Norway Portland, ND other 372 Waukegan, Chicago, IL other 373 Myren, Sweden New York, NY other