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Point Plot
Violinplot
Boxplot
>>> sns.pointplot(x="class",
y="survived", hue="sex",
data=titanic, palette={"male":"g",
"female":"m"}, markers=["^","o"],
linestyles=["-","--"])
>>> sns.violinplot(x="age",
y="sex", hue="survived",
data=titanic)
>>> h = sns.PairGrid(iris)
>>> h = h.map(plt.scatter)
>>> sns.boxplot(x="alive",
y="age", hue="adult_male",
data=titanic)
>>> sns.boxplot
(data=iris,orient="h")
Show point estimates and
confidence intervals as
rectangular bars
Violin plot
Subplot grid for plotting pairwise
relationships
Boxplot
Boxplot with wide-form data](https://image.slidesharecdn.com/mk-250208105035-c32678aa/85/Python-for-data-science-Datascience-Python-4-320.jpg)
![www.1stepgrow.com
Point Plot
Violinplot
Boxplot
>>> sns.pointplot(x="class",
y="survived", hue="sex",
data=titanic, palette={"male":"g",
"female":"m"}, markers=["^","o"],
linestyles=["-","--"])
>>> sns.violinplot(x="age",
y="sex", hue="survived",
data=titanic)
>>> h = sns.PairGrid(iris)
>>> h = h.map(plt.scatter)
>>> sns.boxplot(x="alive",
y="age", hue="adult_male",
data=titanic)
>>> sns.boxplot
(data=iris,orient="h")
Show point estimates and
confidence intervals as
rectangular bars
Violin plot
Subplot grid for plotting pairwise
relationships
Boxplot
Boxplot with wide-form data](https://image.slidesharecdn.com/mk-250208105035-c32678aa/75/Python-for-data-science-Datascience-Python-4-2048.jpg)
Uploaded by1stepgrow
Python for data science! #Datascience #Python
This document provides a cheat sheet for using Seaborn in Python for data visualization, demonstrating various plotting techniques such as scatter plots, bar charts, and boxplots. It includes examples with datasets like Titanic and Iris, showcasing how to create facet grids, conditional relationships, and display statistical information visually. Additionally, it emphasizes the use of different plot types to present categorical and bivariate data clearly.
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Python for data science! #Datascience #Python
- 1. www.1stepgrow.com SEABORN PYTHON FOR PYTHON FOR DATASCIENCE DATA SCIENCE CHEAT SHEET PART- 3
- 2. www.1stepgrow.com Axis Grids >>> g= sns.FacetGrid(titanic, col="survived", row="sex") >>> sns.factorplot(x="pclass", y="survived", hue="sex", data=titanic) >>> sns.lmplot(x="sepal_width", y="sepal_length", hue="species", data=iris) >>> g = g.map(plt.hist,"age") Subplot grid for plotting conditional relationships Draw a categorical plot onto a Facetgrid Plot data and regression model fits across a FacetGrid Plotting With Seaborn
- 3. www.1stepgrow.com Scatterplot Bar Chart Count Plot >>>sns.stripplot(x="species", y="petal_length",data=iris) >>> sns.barplot(x="sex", y="survived", hue="class", data=titanic) >>> sns.countplot(x="deck", data=titanic, palette="Greens_d") >>> sns.swarmplot(x="species", y="petal_length", data=iris) Scatterplot with one categorical variable Show point estimates and confidence intervals with scatterplot glyphs Show count of observations Categorical scatterplot with non-overlapping points Categorical Plots
- 4. www.1stepgrow.com Point Plot Violinplot Boxplot >>> sns.pointplot(x="class", y="survived",hue="sex", data=titanic, palette={"male":"g", "female":"m"}, markers=["^","o"], linestyles=["-","--"]) >>> sns.violinplot(x="age", y="sex", hue="survived", data=titanic) >>> h = sns.PairGrid(iris) >>> h = h.map(plt.scatter) >>> sns.boxplot(x="alive", y="age", hue="adult_male", data=titanic) >>> sns.boxplot (data=iris,orient="h") Show point estimates and confidence intervals as rectangular bars Violin plot Subplot grid for plotting pairwise relationships Boxplot Boxplot with wide-form data
- 5. www.1stepgrow.com >>> i =i.plot(sns.regplot, sns.distplot) >>> sns.jointplot("sepal_length", "sepal_width", data=iris, kind='kde') Plot bivariate distribution >>> sns.pairplot(iris) >>> i = sns.JointGrid(x="x", y="y", data=data) Plot pairwise bivariate distributions Grid for bivariate plot with marginal univariate plots
- 6. www.1stepgrow.com Build your careerstory with 1stepGrow Academy Follow 1stepGrow Academy Save the Post Share your Comments