Seaborn bar plot

The dataset

	total_bill	sex	time	tip	size	day	smoker
0	500.0	male	lunch	30	2	sat	no
1	648.0	male	dinner	35	3	sat	yes
2	75.0	female	lunch	10	1	sat	no
3	159.0	female	dinner	12	4	sat	yes
4	250.0	male	lunch	3	3	mon	no
5	222.0	female	lunch	25	3	mon	yes
6	356.0	male	dinner	30	4	mon	no
7	99.0	female	lunch	5	1	mon	no
8	150.0	male	dinner	4	4	mon	no
9	225.0	female	lunch	38	4	mon	no
10	478.0	female	lunch	28	3	tue	yes
11	320.0	male	dinner	14	3	tue	yes
12	300.0	male	lunch	32	2	tue	yes
13	520.0	male	lunch	33	3	wed	yes
14	367.0	male	dinner	25	3	tue	yes
15	277.0	female	lunch	40	4	wed	yes
16	100.0	female	dinner	6	1	wed	no
17	99.0	male	dinner	40	1	wed	yes
18	199.0	female	lunch	35	3	wed	no
19	288.0	female	dinner	21	2	wed	yes
20	120.0	male	dinner	18	1	thu	yes
21	168.0	male	lunch	15	4	thu	yes
22	120.0	female	dinner	10	3	thu	yes
23	284.0	male	lunch	8	2	thu	yes

How to create a bar plot?

To create a bar plot write module_name.barplot(). Now in the bracket pass the parameters.

Mandatory parameters:

The first parameter is: for x axis value: x="column_name"

The second parameter is: for y axis value: y="column_name"

The third parameter is: for variable name where we stored dataset: data=variable_name.

The fourth parameter is: hue(hue=" column name"). Hue means, for which your x-axis and y-axis values are. Suppose for sex column, you want to see the total bill in days. So use the total bill column on the y-axis and day in the x-axis and sex column in hue.

Extra parameters:

errwidth: value integer. In the bar plot, you will see a straight line on the top of each bar. To edit that line width use this parameter.

errcolor= "color name" . In the bar plot, you will see a straight line on the top of each bar. To edit that line color use this parameter.

ci= int value. In the bar plot, you will see a straight line on the top of each bar. To edit that line size use this parameter.

saturation=value between 0.0-1.0.

palette value name. There is some fixed name for this parameter. You can use those names for different pre-build colors. Example:Accent_r, hot, inferno_r, etc.

linestyle:" --,-.,-,: etc". Used to give the borderline style of bars.

linewidth:"int value". Used to give the borderline width of bars.

alpha:0.0-1.0.

How to give title,labels,legend,grid?
Title
For title write module_name.title().
In the bracket write the title as a string. For font size write fontsize:value. Between title name and fontsize parameter give a coma.

xlabel
For label at x-axis write module_name.ylabel().
In the bracket write label name as string. For font size write fontsize:value. Between label name and fontsize parameter give a coma.

ylabel
For label at y-axis write module_name. ylabel().
In the bracket write label name as string. For fontsize write fontsize:value. Between label name and fontsize parameter give a coma.

grid
For grid first write module_name.grid().
Some parameters of the grid are
1.color: used to set the color of the grid.Example: color="green".
2.linestyle: used to set grid line style.Example: linestyle="--".
3.linewidth: used to set line width of the grid.example: linewidth=2.

set()

This is used to set grid background. To use this write module_name.set().

figure()

This is used to set the size of the plot. To use this write module_name.figure(). In the bracket write figsize=(width,height)

Example 1:

Input
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

df=pd.read_csv("E\\CSV4.csv")
sns.barplot(x="day",y="total_bill",data=df,hue="sex",alpha=0.6,linewidth="4",linestyle=":")
plt.title("Bar plot",fontsize=15)
plt.xlabel("Days",fontsize=12)
plt.ylabel("Total bill",fontsize=15)
plt.show()

Example 2:

Input
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

df=pd.read_csv("E\\CSV4.csv")
sns.barplot(x="day",y="total_bill",data=df,hue="sex",errwidth=7,errcolor="g",saturation=0.5,palette="hot",color="r",ci=10)
plt.show()

Example 3:

Input
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

df=pd.read_csv("E\\CSV4.csv")
sns.barplot(x="day",y="total_bill",data=df,hue="sex")
plt.show()

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