Data Visualization using Matplotlib in Python Part 1 | Python Courses in Tamil | Skillfloor - video Dailymotion

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00:00Hello everyone. In this video, we will talk about data visualization using Matplotlib.

00:10So, when we use Matplotlib, we will talk about different charts.

00:17First, we will load a dataset.

00:19From SQL.dataset, import load iris.

00:22Pandas library, we will import.

00:24Next, iris equal to load underscore iris.

00:27So, this is actually a dictionary format.

00:31Load iris.

00:34Actually, iris dataset is a dictionary format.

00:39Key is data.

00:41This is sepal length, sepal width, petal length, petal width.

00:44So, there are 4 data.

00:46This is row data.

00:49Then, target column.

00:52So, if we use 4 values, target column 0, 1, 2 are.

00:56That is plus 0 represent setosa.

00:591 is versical.

01:002 is virginica.

01:01And, this is feature names.

01:06Sepal length, sepal width, petal length, petal width.

01:09That is the 4 values.

01:10That is the data.

01:11This is base.

01:12We will create data frame.

01:14So, df equal to pd.dataframe.

01:17Data equal to iris of data.

01:19Iris enter the dictionary.

01:21So, we use data frame.

01:24So, data equal to iris of data.

01:26Columns equal to iris of feature names.

01:29So, the first column we will create.

01:32Now, we will create a new column.

01:34We will create a new column.

01:35That is, df of species is equal to iris of target.

01:38Then, target is 0, 1, 2.

01:40Normal.

01:42Target equal to 0, 0, 0.

01:45Now, this is normal setosa represent.

01:501 is versical, 2 is versical.

01:52So, if we compare it to df of species is equal to df of species.map of 0, setosa.

01:59That is the result.

02:00That is the result.

02:01That is the result.

02:02Next is 0.

02:03So, setosa is the result.

02:041 is versical, 2 is versical.

02:06So, we will create a new column.

02:07So, in the map, we will create a new data set.

02:09So, we will create a new data set.

02:11So, we will create a new plot.

02:12The first plot, we will analyze the first line plot.

02:15So, first, what do we do in the line chart?

02:21What do we do in the line?

02:22We will create a new column.

02:23We will create a new column.

02:24We will create a new column.

02:25That is, Cepalent and Petalent.

02:30Now, this is the first data.

02:32This is 1.

02:33This is 2.

02:34This is 3.

02:35This is 4.

02:37This is 5.

02:38This is 6 and 7.

02:43So, we will create a new order.

02:46We will create a new order.

02:473, 4, 5, 6, 7.

02:50So, in the line chart, we will plot.

02:53There is a proper visualization.

02:55If we can do it,

02:56we will sort it.

02:58So, df of sorted is equal to

03:01df.sort values of Cepalent.

03:03So, Cepalent length.

03:05We will sort it.

03:06We will sort it.

03:07Sort it.

03:08So, plot.

03:09Normally, we will determine the line plot.

03:12So, line plot create.

03:14What is this?

03:15This is x-axis.

03:16First data, x-axis.

03:17Second data, y-axis.

03:19So, Cepalent, Petal length.

03:21Then, this value system.

03:22This value system.

03:23This plot is normal.

03:24In the one-toon order.

03:26This x-axis, y-axis.

03:27This point is x, y value.

03:30That is Cepalent and Petal length.

03:32Then, this is Cepalent and Petal length.

03:34So, in the dots,

03:36we will see the points.

03:37We will see the points.

03:38The points are the markers equal to oval.

03:40The other color is blue.

03:42Let's change the color.

03:43Next, I will have the title.

03:45Cepalent vs Petal length.

03:47Then, we will see the already introduction.

03:51We will do the mat plot.

03:52We will specify the little add-tration.

03:55We will specify the x-axis.

03:58That is x-axis.

03:59We will see the plot.x-label of Cepalent.

04:02The plot.y-label of y-axis data.

04:04We will provide the y-labeling.

04:06Petal length.

04:07Then, we will store the grid format.

04:09We will activate the plot.grid.

04:12The grid is important.

04:14We will visualize the exact point.

04:18We will analyze the exact point.

04:20We will analyze the exact point.

04:22So, we will consider the point.

04:24So, this is Cepal length.

04:265.

04:28Then,

04:29Petal length is 3.5.

04:32Then, we will use the grid line.

04:34So, we will activate the grid line.

04:36So, we will activate the grid line.

04:38So, we will activate the grid line.

04:42This is a normal line plot.

04:44Create the plot.

04:45The data visualization using matplotlib part 1 is the next video in the next video.

04:58You

Data Visualization using Matplotlib in Python Part 1 | Python Courses in Tamil | Skillfloor

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