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# Python Data Visualisation for Business Analyst – How to Plot Multiple Time Series in Python

In this data visualisation tutorial, you will learn – How to Plot Multiple Time Series in Python.

You can plot multiple time series that measures the same value on the same chart as shown below.

## Setup

Run this once before the plot’s code. The individual charts, however, may redefine its own aesthetics.

``````/* !pip install brewer2mpl */
import numpy as np
import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
import warnings; warnings.filterwarnings(action='once')

large = 22; med = 16; small = 12
params = {'axes.titlesize': large,
'legend.fontsize': med,
'figure.figsize': (16, 10),
'axes.labelsize': med,
'axes.titlesize': med,
'xtick.labelsize': med,
'ytick.labelsize': med,
'figure.titlesize': large}
plt.rcParams.update(params)
plt.style.use('seaborn-whitegrid')
sns.set_style("white")
%matplotlib inline

/* Version */
print(mpl.__version__)
print(sns.__version__)``````
Data: mortality

## How to do Time Series Decomposition Plot in Python

``````/* Import Data */

/* Define the upper limit, lower limit, interval of Y axis and colors */
y_LL = 100
y_UL = int(df.iloc[:, 1:].max().max()*1.1)
y_interval = 400
mycolors = ['tab:red', 'tab:blue', 'tab:green', 'tab:orange']

/* Draw Plot and Annotate */
fig, ax = plt.subplots(1,1,figsize=(16, 9), dpi= 80)

columns = df.columns[1:]
for i, column in enumerate(columns):
plt.plot(df.date.values, df[column].values, lw=1.5, color=mycolors[i])
plt.text(df.shape[0]+1, df[column].values[-1], column, fontsize=14, color=mycolors[i])

/* Draw Tick lines */
for y in range(y_LL, y_UL, y_interval):
plt.hlines(y, xmin=0, xmax=71, colors='black', alpha=0.3, linestyles="--", lw=0.5)

/* Decorations  */
plt.tick_params(axis="both", which="both", bottom=False, top=False,
labelbottom=True, left=False, right=False, labelleft=True)

/* Lighten borders */
plt.gca().spines["top"].set_alpha(.3)
plt.gca().spines["bottom"].set_alpha(.3)
plt.gca().spines["right"].set_alpha(.3)
plt.gca().spines["left"].set_alpha(.3)

plt.title('Number of Deaths from Lung Diseases in the UK (1974-1979)', fontsize=22)
plt.yticks(range(y_LL, y_UL, y_interval), [str(y) for y in range(y_LL, y_UL, y_interval)], fontsize=12)
plt.xticks(range(0, df.shape[0], 12), df.date.values[::12], horizontalalignment='left', fontsize=12)
plt.ylim(y_LL, y_UL)
plt.xlim(-2, 80)
plt.show()``````

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