In this article, we’ll perceive how to add another line of qualities to a current dataframe. This can be utilized when we need to embed another passage in our information that we may have missed adding before. There are various strategies to accomplish this. Presently we should see with the assistance of models how we can do this
To annex or add a column to DataFrame, make the new line as Series and use DataFrame.append() strategy. In this instructional exercise, we will figure out how to attach a line to a current DataFrame, with the assistance of illustrative model projects.
Example 1:
from IPython.display import display, HTML import pandas as pd from numpy.random import randint dict = { 'Name' :[ 'Martha' , 'Tim' , 'Rob' , 'Georgia' ], 'Maths' :[ 87 , 91 , 97 , 95 ], 'Science' :[ 83 , 99 , 84 , 76 ] } df = pd.DataFrame( dict ) display(df) df.loc[ len (df.index)] = [ 'Amy' , 89 , 93 ] display(df) |
Output:
Example 2:
from IPython.display import display, HTML import pandas as pd import numpy as np dict = { 'Name' :[ 'Martha' , 'Tim' , 'Rob' , 'Georgia' ], 'Maths' :[ 87 , 91 , 97 , 95 ], 'Science' :[ 83 , 99 , 84 , 76 ] } df = pd.DataFrame( dict ) display(df) df2 = { 'Name' : 'Amy' , 'Maths' : 89 , 'Science' : 93 } df = df.append(df2, ignore_index = True ) display(df) |
Output:
Example 3:
from IPython.display import display, HTML import pandas as pd import numpy as np dict = { 'Name' :[ 'Martha' , 'Tim' , 'Rob' , 'Georgia' ], 'Maths' :[ 87 , 91 , 97 , 95 ], 'Science' :[ 83 , 99 , 84 , 76 ] } df1 = pd.DataFrame( dict ) display(df1) dict = { 'Name' :[ 'Amy' , 'Maddy' ], 'Maths' :[ 89 , 90 ], 'Science' :[ 93 , 81 ] } df2 = pd.DataFrame( dict ) display(df2) df3 = pd.concat([df1, df2], ignore_index = True ) df3.reset_index() display(df3) |
Output: