Pandas is a data analysis and manipulation module that helps you load and parse data. That is a module you'll probably use when creating plots.
In Pandas, data is stored in data frames. For instance, if you load data from Excel. Of course you don't have to use Pandas when working with data, just as you don't have to use a car when travelling. But it makes working with data much easier.
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example
seaborn pandas
The seaborn pandas plot is created from the . The data frame uses random data, but in practice this data often comes from databases, Excel or other sources.
The program creates different plots but for simplicity only one result is shown.
import numpy as np
import pandas as pd
from scipy import stats
import matplotlib.pyplot as plt
import seaborn as sns
df_obj1 = pd.DataFrame({"x": np.random.randn(500),
"y": np.random.randn(500)})
df_obj2 = pd.DataFrame({"x": np.random.randn(500),
"y": np.random.randint(0, 100, 500)})
sns.jointplot(x="x", y="y", data=df_obj2)
sns.jointplot(x="x", y="y", data=df_obj2, kind="hex");
sns.jointplot(x="x", y="y", data=df_obj1, kind="kde");
dataset = sns.load_dataset("tips")
sns.pairplot(dataset);
#titanic = sns.load_dataset('titanic')
#planets = sns.load_dataset('planets')
#flights = sns.load_dataset('flights')
#iris = sns.load_dataset('iris')
exercise = sns.load_dataset('exercise')
sns.stripplot(x="diet", y="pulse", data=exercise)
sns.swarmplot(x="diet", y="pulse", data=exercise, hue='kind')
sns.boxplot(x="diet", y="pulse", data=exercise)
sns.boxplot(x="diet", y="pulse", data=exercise, hue='kind')
sns.violinplot(x="diet", y="pulse", data=exercise, hue='kind')
sns.barplot(x="diet", y="pulse", data=exercise, hue='kind')
sns.pointplot(x="diet", y="pulse", data=exercise, hue='kind');
plt.show()
Practice now: Test your Python skills with interactive challenges