Last Updated : 11 Dec, 2020
In this article, we will learn how to create A Time Series Plot With Seaborn And Pandas. Let's discuss some concepts :
Here, we create a rough data for understanding the time series plot with the help of some examples. Let's create the data :
Python3
# importing packages
import pandas as pd
# creating data
df = pd.DataFrame({'Date': ['2019-10-01', '2019-11-01',
'2019-12-01','2020-01-01',
'2020-02-01', '2020-03-01',
'2020-04-01', '2020-05-01',
'2020-06-01'],
'Col_1': [34, 43, 14, 15,
15, 14, 31, 25, 62],
'Col_2': [52, 66, 78, 15, 15,
5, 25, 25, 86],
'Col_3': [13, 73, 82, 58, 52,
87, 26, 5, 56],
'Col_4': [44, 75, 26, 15, 15,
14, 54, 25, 24]})
# view dataset
display(df)
Output:
Example 1: Simple time series plot with single column using lineplot
Python3
# importing packages
import seaborn as sns
import pandas as pd
# creating data
df = pd.DataFrame({'Date': ['2019-10-01', '2019-11-01',
'2019-12-01','2020-01-01',
'2020-02-01', '2020-03-01',
'2020-04-01', '2020-05-01',
'2020-06-01'],
'Col_1': [34, 43, 14, 15, 15,
14, 31, 25, 62],
'Col_2': [52, 66, 78, 15, 15,
5, 25, 25, 86],
'Col_3': [13, 73, 82, 58, 52,
87, 26, 5, 56],
'Col_4': [44, 75, 26, 15, 15,
14, 54, 25, 24]})
# create the time series plot
sns.lineplot(x = "Date", y = "Col_1",
data = df)
plt.xticks(rotation = 25)
Output :
Example 2: (Simple time series plot with multiple columns using line plot)
Python3
# importing packages
import seaborn as sns
import pandas as pd
# creating data
df = pd.DataFrame({'Date': ['2019-10-01', '2019-11-01',
'2019-12-01','2020-01-01',
'2020-02-01', '2020-03-01',
'2020-04-01', '2020-05-01',
'2020-06-01'],
'Col_1': [34, 43, 14, 15, 15,
14, 31, 25, 62],
'Col_2': [52, 66, 78, 15, 15,
5, 25, 25, 86],
'Col_3': [13, 73, 82, 58, 52,
87, 26, 5, 56],
'Col_4': [44, 75, 26, 15, 15,
14, 54, 25, 24]})
# create the time series plot
sns.lineplot(x = "Date", y = "Col_1", data = df)
sns.lineplot(x = "Date", y = "Col_2", data = df)
plt.ylabel("Col_1 and Col_2")
plt.xticks(rotation = 25)
Output :
Example 3: Multiple time series plot with multiple columns
Python3
# importing packages
import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt
# creating data
df = pd.DataFrame({'Date': ['2019-10-01', '2019-11-01',
'2019-12-01','2020-01-01',
'2020-02-01', '2020-03-01',
'2020-04-01', '2020-05-01',
'2020-06-01'],
'Col_1': [34, 43, 14, 15, 15,
14, 31, 25, 62],
'Col_2': [52, 66, 78, 15, 15,
5, 25, 25, 86],
'Col_3': [13, 73, 82, 58, 52,
87, 26, 5, 56],
'Col_4': [44, 75, 26, 15, 15,
14, 54, 25, 24]})
# create the time series subplots
fig,ax = plt.subplots( 2, 2,
figsize = ( 10, 8))
sns.lineplot( x = "Date", y = "Col_1",
color = 'r', data = df,
ax = ax[0][0])
ax[0][0].tick_params(labelrotation = 25)
sns.lineplot( x = "Date", y = "Col_2",
color = 'g', data = df,
ax = ax[0][1])
ax[0][1].tick_params(labelrotation = 25)
sns.lineplot(x = "Date", y = "Col_3",
color = 'b', data = df,
ax = ax[1][0])
ax[1][0].tick_params(labelrotation = 25)
sns.lineplot(x = "Date", y = "Col_4",
color = 'y', data = df,
ax = ax[1][1])
ax[1][1].tick_params(labelrotation = 25)
fig.tight_layout(pad = 1.2)
Output :
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