Data visualizations in Python for data science:

1)Line plot:
Importing the libraries and loading the datset:
 

Importing libraries and loading the dataset

Printing first five rows:

Printing first five rows

 
Line plot between timeplot and signal:

Lineplot in seaborn

 
Line plot with hue parameter:

Hue parameter takes column name for colour encoding.

Line plot with hue parameter

 

Line plot with hue parameter, style and markers:

Lineplot with hue, style and markers

 
2) Barplot:
Loading the diabetes dataset and printing the first five columns:

Loading the dataset

 
Plotting barplot between the columns outcome and insulin:

Barplot in seaborn

 
Plotting barplot and adding palette as bright:

Barplot with palette

 
3) Scatter plot:
Loading iris dataset:

Loading the dataset

 
Scatter plot between columns sepal_width and petal_width with hue as species:

Scatterplot in seaborn

 
4) Histplot/distplot:
Loading "taxis" dataset:

Loading dataset

 
Printing histogram and frequency curve on column fare:

Histogram and frequency curve

 
Printing only frequency curve on column fare by making hist false:

Printing only frequency curve

 
Printing histogram frequency curve on column fare and adding color:

Histogram and frequency curve by adding color

 
Printing only histogram on column fare and adding color:

Only histogram with colors

 
Printing only histogram on column fare and adding color and bin size:

Histogram with bins

 
Printing vertical histogram on column fare and adding color and number of bins :

Vertical histogram

 
5) Boxplot:
Loading "tips" dataset and printing first five columns:

Loading tips dataset

 
Printing boxplot on columns sex and total_bill:

Boxplot in seaborn

 
Printing boxplot and adding hue and palette:
 

Boxplot with hue and palette