1 00:00:00,840 --> 00:00:07,290 In this video, we will learn how to handle the missing values in our dataset, handling missing values 2 00:00:07,290 --> 00:00:14,100 is very important since most of the models cannot run if there is some missing value in our data said. 3 00:00:16,140 --> 00:00:22,830 We saw how to find out the missing value using the descriptive statistics option, and we found out 4 00:00:22,950 --> 00:00:27,420 that and housemaid's variable contains some missing values. 5 00:00:30,270 --> 00:00:36,510 To look at the missing values, we will again use these filtering options if you have not applied filters 6 00:00:36,660 --> 00:00:37,170 to law. 7 00:00:38,540 --> 00:00:46,940 To apply filters, you have to select the top row of the table and go to data and click on this filter 8 00:00:46,940 --> 00:00:47,330 option. 9 00:00:50,320 --> 00:00:57,730 Now that you have these filtering options, click on the small triangle of enhancement, then scroll 10 00:00:57,730 --> 00:01:06,310 down and you will find these this Blancs option, this blancs is giving us all those cells which do 11 00:01:06,310 --> 00:01:07,750 not contain any value. 12 00:01:08,950 --> 00:01:13,890 So first, we will undertake all of these cells back and checking the select button. 13 00:01:14,740 --> 00:01:16,990 Then we will take this Blancs option. 14 00:01:19,140 --> 00:01:25,180 You can see we get eight observations which do not have value for inhospitable variable. 15 00:01:27,390 --> 00:01:34,980 As we have learned in antireligious, depending on the business knowledge, we can use mean median maximum 16 00:01:35,160 --> 00:01:38,880 or zero as the replacement for these missing values. 17 00:01:40,840 --> 00:01:46,510 For now, we are going to use the mean value of this variable to replace the missing values. 18 00:01:48,280 --> 00:01:54,280 To find the main values, we will again go to these filtering options and select all the values. 19 00:01:57,040 --> 00:01:58,110 Delectably, values. 20 00:02:00,380 --> 00:02:08,840 Ed, we will rate average to this function will give us the average of all the values. 21 00:02:14,770 --> 00:02:17,530 To select all the values and hit enter. 22 00:02:20,990 --> 00:02:28,700 So this seven point eight nine nine is the average of all the values of enhanced BERRIDGE variable. 23 00:02:30,030 --> 00:02:35,730 We will use this value to replace the missing values, so copy this value. 24 00:02:39,600 --> 00:02:42,660 Then click this icon and select only the blank values. 25 00:02:46,430 --> 00:02:54,550 And paste this value in each of these blankets, but while pasting, you have to place this as values. 26 00:02:55,490 --> 00:02:59,100 So the second option in posting options is values. 27 00:02:59,240 --> 00:03:01,910 Click on this to paste the value of this. 28 00:03:01,910 --> 00:03:08,540 Otherwise you will paste formula here, which will give you the long value of the average to right click 29 00:03:08,540 --> 00:03:15,050 on this will go to place options and to link this second image of basters values. 30 00:03:18,030 --> 00:03:25,440 So now we have replaced all the blank values with the mean, if I remove the filter and select all. 31 00:03:27,060 --> 00:03:29,820 Now if I go, there will be no blank value in it. 32 00:03:32,370 --> 00:03:36,930 So we have handled the missing values and this and housemaid's variable. 33 00:03:38,720 --> 00:03:44,870 If in your dataset there are other variables which have some missing values, you need to treat all 34 00:03:44,870 --> 00:03:53,090 those variables, apply the filter and select the blanks in that column, change the values of those 35 00:03:53,090 --> 00:04:00,080 blanks to mean median max, whichever is the business scenario for those missing values.