WEBVTT 00:00.590 --> 00:06.560 Welcome come to the solution for coding exercise for and we have already imparted pandas and also the 00:06.560 --> 00:11.190 listings data set and an exercise 31. 00:11.240 --> 00:18.470 We have to select the arrow index or the roll labels of our data frame listings and we can simply do 00:18.470 --> 00:26.520 this with the index attribute and here we have a Range Index from zero to six thousand eight hundred 00:26.520 --> 00:27.700 fifty two. 00:27.720 --> 00:34.170 Then the next question we have to set the symbol columns of the new index and we can do this the rest 00:34.170 --> 00:39.330 of the set index method and we pass the column later symbol. 00:39.690 --> 00:44.190 And as we want to save for the change we have to pass through to the in-place parameter 00:47.170 --> 00:53.500 and then next we have to check whether the new index or the symbol index contains the unique values 00:53.530 --> 01:04.080 only and no duplicates and we can check this here with the is the unique attribute on the index until 01:04.120 --> 01:04.950 we get a fourth. 01:04.950 --> 01:09.860 So there are apparently duplicates in the index. 01:10.030 --> 01:17.160 And the reason for this is that we have a few companies and a few tickers that are actually listed on 01:17.170 --> 01:19.230 more than one exchange. 01:19.240 --> 01:26.830 So for example on the Nasdaq and the Amex then next year and exercise 35 we should get to the frequency 01:26.830 --> 01:28.960 of the index elements. 01:28.960 --> 01:30.700 And again here we use. 01:30.760 --> 01:33.520 The value counts method on the index 01:37.860 --> 01:42.150 and we have to take us off the companies that are listed on more than one exchange. 01:42.150 --> 01:49.150 So on two exchanges here and finally we can also set a name for our index. 01:49.150 --> 01:55.960 For example the ticker symbol and we can do this by setting the index names so that in addition the 01:56.380 --> 01:58.540 attribute name on our index. 01:58.630 --> 02:03.760 So we set the name here to a ticker symbol and let's have a look here. 02:03.760 --> 02:10.020 So here on the left hand side we can see that here we have the name ticker symbol and finally we can 02:10.020 --> 02:13.240 also reset to the index and create a range index. 02:13.320 --> 02:19.740 With the reset index method and as the we want to save the change also here we have to pass through 02:19.740 --> 02:21.180 to the in-place parameter 02:24.510 --> 02:29.810 and again here we are on the left hand side a Range Index and our form formal index the ticker symbol 02:29.830 --> 02:38.720 is now a column of our data frame and with the columns attribute we can also therefore look at the Columns 02:38.730 --> 02:48.530 index so here we have the column labels the ticker symbol exchanged name and so on and we can also rename 02:48.530 --> 02:50.780 some of these column labels. 02:50.990 --> 02:57.920 So let's assume that you want to rename the column label name to company and market cap to m cap then 02:57.920 --> 03:04.100 we can do the same with the rename method and we determine that you want to change column labels so 03:04.100 --> 03:10.650 we use your columns parameter and then we pass a dictionary both on the left hand side. 03:10.700 --> 03:12.050 The old labels. 03:12.050 --> 03:13.700 So name and market cap. 03:13.700 --> 03:16.230 And that's actually the case of the dictionary. 03:16.400 --> 03:23.630 And as the values of the dictionary we have the new names company and M cap and again will be passed 03:23.760 --> 03:30.080 through to the in-place pair of meta and let's have a look here so here we have successfully changed 03:30.180 --> 03:37.080 the column labels to company and M cap and uh with this we are finished with the solution. 03:37.080 --> 03:42.030 I hope you had fun and uh looking forward to seeing you also in exercise five by.