lollipop plot using seaborn library with python

# libraries
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
 
# Create a dataframe
df = pd.DataFrame({'group':list(map(chr, range(65, 85))), 'values':np.random.uniform(size=20) })
 
# Reorder it following the values:
ordered_df = df.sort_values(by='values')
my_range=range(1,len(df.index)+1)
 
# The vertival plot is made using the hline function
# I load the seaborn library only to benefit the nice looking feature
import seaborn as sns
plt.hlines(y=my_range, xmin=0, xmax=ordered_df['values'], color='skyblue')
plt.plot(ordered_df['values'], my_range, "o")
 
# Add titles and axis names
plt.yticks(my_range, ordered_df['group'])
plt.title("A vertical lolipop plot", loc='left')
plt.xlabel('Value of the variable')
plt.ylabel('Group')

Out[2]:

Text(0, 0.5, 'Group')

In [7]:

# libraries
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
 
# Create a dataframe
df = pd.DataFrame({'group':list(map(chr, range(65, 85))), 'values':np.random.uniform(size=20) })
 
# Reorder it following the values:
ordered_df = df.sort_values(by='values')
my_range=range(1,len(df.index)+1)
 
# The vertival plot is made using the hline function
# I load the seaborn library only to benefit the nice looking feature
import seaborn as sns
plt.hlines(y=my_range, xmin=0, xmax=ordered_df['values'], color='blue')
plt.plot(ordered_df['values'], my_range, "o")
 
# Add titles and axis names
plt.yticks(my_range, ordered_df['group'])
plt.title("A vertical lolipop plot", loc='left')
plt.xlabel('Value of the variable')
plt.ylabel('Group')

Out[7]:

Text(0, 0.5, 'Group')

In [ ]: