How can i replace the values of a column for a specific observation to zero?

General
#1

Hi, I would like to replace the values of a column for a specific observation to zero.
this is my data frame:
structure(list(Year = c(2017, 2017, 2017, 2017, 2017, 2017, 2017,
2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017,
2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017,
2017, 2017, 2017, 2017, 2017, 2017, 2017), Quartal = c("2017-Q1",
"2017-Q2", "2017-Q3", "2017-Q4", "2017-Q1", "2017-Q2", "2017-Q3",
"2017-Q4", "2017-Q4", "2017-Q2", "2017-Q3", "2017-Q4", "2017-Q1",
"2017-Q2", "2017-Q3", "2017-Q4", "2017-Q1", "2017-Q4", "2017-Q2",
"2017-Q3", "2017-Q4", "2017-Q4", "2017-Q1", "2017-Q2", "2017-Q3",
"2017-Q4", "2017-Q1", "2017-Q2", "2017-Q3", "2017-Q4", "2017-Q1",
"2017-Q2", "2017-Q3", "2017-Q4", "2017-Q4", NA), City = c("London",
"London", "London", "London", "London", "London", "London", "London",
"London", "London", "London", "London", "London", "London", "London",
"London", "Paris", "Paris", "Paris", "Paris", "Paris", "Paris",
"Paris", "Paris", "Paris", "Paris", "Rome", "Rome", "Rome", "Rome",
"Rome", "Rome", "Rome", "Rome", "Rome", "Rome"), Department = c("Male",
"Male", "Male", "Male", "Female", "Female", "Female", "Female",
"Child", "Home", "Home", "Home", "Garden", "Garden", "Garden",
"Garden", "Male", "Male", "Female", "Female", "Female", "Child",
"Garden", "Garden", "Garden", "Garden", "Male", "Male", "Male",
"Male", "Female", "Female", "Female", "Female", "Child", "Total"
), TotalSales = c("56", "81", "103", "88", "368", "296", "369",
"324", "103", "230", "225", "334", "787", "806", "925", "918",
"242", "287", "156", "161", "169", "Depart", "76", "62", "66",
"70", "1176", "1185", "1432", "1408", "1376", "1492", "1830",
"1628", "289", "19118"), TotalDamage = c("2", "2", "1", "2",
"9", "4", "4", "3", "1", "7", "6", "11", "2", "4", "5", "4",
"NA", "NA", "NA", "NA", "NA", "2", "NA", "NA", "NA", "NA", "NA",
"NA", "4", "1", "34", "19", "40", "37", "6", "210"), TotalDamagePercent = c(3.57,
2.46, 9.7, 2.72, 2.44, 1.35, 1.08, 9.25, 9.7, 3.04, 2.66, 3.29,
2.54, 4.96, 5.4, 4.35, 0, 0, 0, 0, 0, 7.43, 0, 0, 0, 0, 0, 0,
2.79, 7.1, 2.47, 1.27, 2.18, 2.27, 2.07, 0.96)), class = "data.frame", row.names = c(NA,
-36L))

I would like to replace all the "TotalSales" and "TotalDamage"from London to zero and from Rome just the "TotalDamage"to zero

I have tried to replace, but it did not work.

Any ideas?

Thanks very much in advance

1 Like
#2

Hi,

DFF_modified <- DFF
DFF_modified$TotalSales <- ifelse(DFF_modified$City == "London", 0, DFF_modified$TotalSales)
DFF_modified$TotalDamage <- ifelse(DFF_modified$City == "London", 0, ifelse(DFF_modified$City == "Rome", 0, DFF_modified$TotalDamage))

# Year Quartal   City Department TotalSales TotalDamage TotalDamagePercent
# 1  2017 2017-Q1 London       Male          0           0               3.57
# 2  2017 2017-Q2 London       Male          0           0               2.46
# 3  2017 2017-Q3 London       Male          0           0               9.70
# 4  2017 2017-Q4 London       Male          0           0               2.72
# 5  2017 2017-Q1 London     Female          0           0               2.44
# 6  2017 2017-Q2 London     Female          0           0               1.35
# 7  2017 2017-Q3 London     Female          0           0               1.08
# 8  2017 2017-Q4 London     Female          0           0               9.25
# 9  2017 2017-Q4 London      Child          0           0               9.70
# 10 2017 2017-Q2 London       Home          0           0               3.04
# 11 2017 2017-Q3 London       Home          0           0               2.66
# 12 2017 2017-Q4 London       Home          0           0               3.29
# 13 2017 2017-Q1 London     Garden          0           0               2.54
# 14 2017 2017-Q2 London     Garden          0           0               4.96
# 15 2017 2017-Q3 London     Garden          0           0               5.40
# 16 2017 2017-Q4 London     Garden          0           0               4.35
# 17 2017 2017-Q1  Paris       Male        242          NA               0.00
# 18 2017 2017-Q4  Paris       Male        287          NA               0.00
# 19 2017 2017-Q2  Paris     Female        156          NA               0.00
# 20 2017 2017-Q3  Paris     Female        161          NA               0.00
# 21 2017 2017-Q4  Paris     Female        169          NA               0.00
# 22 2017 2017-Q4  Paris      Child     Depart           2               7.43
# 23 2017 2017-Q1  Paris     Garden         76          NA               0.00
# 24 2017 2017-Q2  Paris     Garden         62          NA               0.00
# 25 2017 2017-Q3  Paris     Garden         66          NA               0.00
# 26 2017 2017-Q4  Paris     Garden         70          NA               0.00
# 27 2017 2017-Q1   Rome       Male       1176           0               0.00
# 28 2017 2017-Q2   Rome       Male       1185           0               0.00
# 29 2017 2017-Q3   Rome       Male       1432           0               2.79
# 30 2017 2017-Q4   Rome       Male       1408           0               7.10
# 31 2017 2017-Q1   Rome     Female       1376           0               2.47
# 32 2017 2017-Q2   Rome     Female       1492           0               1.27
# 33 2017 2017-Q3   Rome     Female       1830           0               2.18
# 34 2017 2017-Q4   Rome     Female       1628           0               2.27
# 35 2017 2017-Q4   Rome      Child        289           0               2.07
# 36 2017    <NA>   Rome      Total      19118           0               0.96
1 Like
#3

Thanks very much @M_AcostaCH it works perfect!

1 Like
#4

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