import pandas as pd
import seaborn as sns

df = sns.load_dataset("titanic")
df.head()

	survived	pclass	sex	age	sibsp	parch	fare	embarked	class	who	adult_male	deck	embark_town	alive	alone
0	0	3	male	22.0	1	0	7.2500	S	Third	man	True	NaN	Southampton	no	False
1	1	1	female	38.0	1	0	71.2833	C	First	woman	False	C	Cherbourg	yes	False
2	1	3	female	26.0	0	0	7.9250	S	Third	woman	False	NaN	Southampton	yes	True
3	1	1	female	35.0	1	0	53.1000	S	First	woman	False	C	Southampton	yes	False
4	0	3	male	35.0	0	0	8.0500	S	Third	man	True	NaN	Southampton	no	True

sns.barplot(x = "sex", y= "age",hue = "survived" ,data = df)

<Axes: xlabel='sex', ylabel='age'>

sns.stripplot(x="class", y= "age",hue = "sex", data = df)

<Axes: xlabel='class', ylabel='age'>

# x = pd.crosstab(columns=[df["class"],df["survived"],df["age"]] , index=df["sex"])  ## to draw the pivot table
x=pd.crosstab(columns=df["class"],index=df["survived"])

x

class	First	Second	Third
survived
0	80	97	372
1	136	87	119

sns.heatmap(x,annot= True, fmt = ".1f")

<Axes: xlabel='class', ylabel='survived'>

df2 = sns.load_dataset("iris")
df2.head()

	sepal_length	sepal_width	petal_length	petal_width	species
0	5.1	3.5	1.4	0.2	setosa
1	4.9	3.0	1.4	0.2	setosa
2	4.7	3.2	1.3	0.2	setosa
3	4.6	3.1	1.5	0.2	setosa
4	5.0	3.6	1.4	0.2	setosa

df2.head(10).plot(kind = "bar")

<Axes: >

df2.head(10).plot(kind = "bar", stacked = True)

<Axes: >

sns.pairplot(df)
# univariate makes histogram
# bivariate makes scatterplot

<seaborn.axisgrid.PairGrid at 0x184cf032d10>

sns.pairplot(df2)
# univariate makes histogram
# bivariate makes scatterplot

<seaborn.axisgrid.PairGrid at 0x184d48ee390>