In [17]:
#Adjusting the cell width and margin
from IPython.display import display, HTML
display(HTML(data="""
<style>
div#notebook-container { width: 100%; }
div#notebook-container { margin-left: -2.8%; }
div#menubar-container { width: 65%; }
div#maintoolbar-container { width: 99%; }
</style>
"""))
In [ ]:
# Importing the libraries
import pandas as pd
import numpy as np
In [18]:
# Creating a sample data frame
df=pd.DataFrame(np.array(
[['Production','Production','Production',
'Sales','Sales','Sales'],
[10,20,30,15,14,50]])).T
df.columns=['Department','Salary']
df
Out[18]:
In [13]:
# Find the highest salary from each dept
# Step 1:Sort the data frame based on
# Department and Salary
# Step 2:Use group by on Department
# and get the first record
In [15]:
df2=df.sort_values(by = ['Department','Salary'],ascending=False)
df2
Out[15]:
In [16]:
df2.groupby('Department').head(1)
Out[16]:
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