Graph show in python

Categorical variables

BarPlots

In [1]:

import seaborn as sns

import matplotlib.pyplot as plt

sns.set_theme(style="ticks",color_codes=True)

titanic = sns.load_dataset("titanic") #it will load built-in data from seaborn library stored as titanic.

sns.catplot(x="sex", y="survived", hue="class", kind="bar", data=titanic)

plt.show()

Count Plots

In [2]:

import seaborn as sns

import matplotlib.pyplot as plt

sns.set_theme(style="ticks",color_codes=True)

titanic = sns.load_dataset("titanic")

p1 = sns.countplot(x="sex", data=titanic, hue="class")

p1.set_title("Plot for Counting")

plt.show()

Continuous variables

Scatter Plot

In [3]:

import seaborn as sns

import matplotlib.pyplot as plt

sns.set_theme(style="ticks",color_codes=True)

titanic = sns.load_dataset("titanic")

g=sns.FacetGrid(titanic, row="sex", hue="alone")

g=(g.map(plt.scatter, "age", "fare").add_legend())

plt.show()

Only Numeric Data Show

In [4]:

import seaborn as sns

import matplotlib.pyplot as plt

sns.set_theme(style="ticks",color_codes=True)

titanic = sns.load_dataset("titanic")

print(titanic)

     survived  pclass     sex   age  sibsp  parch     fare embarked   class  \

0           0       3    male  22.0      1      0   7.2500        S   Third   

1           1       1  female  38.0      1      0  71.2833        C   First   

2           1       3  female  26.0      0      0   7.9250        S   Third   

3           1       1  female  35.0      1      0  53.1000        S   First   

4           0       3    male  35.0      0      0   8.0500        S   Third   

..        ...     ...     ...   ...    ...    ...      ...      ...     ...   

886         0       2    male  27.0      0      0  13.0000        S  Second   

887         1       1  female  19.0      0      0  30.0000        S   First   

888         0       3  female   NaN      1      2  23.4500        S   Third   

889         1       1    male  26.0      0      0  30.0000        C   First   

890         0       3    male  32.0      0      0   7.7500        Q   Third   



       who  adult_male deck  embark_town alive  alone  

0      man        True  NaN  Southampton    no  False  

1    woman       False    C    Cherbourg   yes  False  

2    woman       False  NaN  Southampton   yes   True  

3    woman       False    C  Southampton   yes  False  

4      man        True  NaN  Southampton    no   True  

..     ...         ...  ...          ...   ...    ...  

886    man        True  NaN  Southampton    no   True  

887  woman       False    B  Southampton   yes   True  

888  woman       False  NaN  Southampton    no  False  

889    man        True    C    Cherbourg   yes   True  

890    man        True  NaN   Queenstown    no   True  



[891 rows x 15 columns]

Adaption of Data

In [7]:

import seaborn as sns

import matplotlib.pyplot as plt

sns.set_theme(style="ticks",color_codes=True)

titanic = sns.load_dataset("titanic")

p1 = sns.countplot(x="who", data=titanic, hue="alone")

p1.set_title("Plot for Counting")

plt.show()

Graphs and Data Sets in Python

Graph show in python

Categorical variables

BarPlots

Count Plots

Continuous variables

Scatter Plot

Only Numeric Data Show

Adaption of Data

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