In this article, we will discuss different ways to create a Pandas DataFrame and append one row at a time in it.
Table Of Contents
What is a DataFrame?
Pandas DataFrame is two dimensional data structure , potentially heterogeneous tabular data structure with three elements : data, rows and columns.
How to Create DataFrame
There are three different ways to create DataFrame in Pandas. First, we will discuss different ways to create Pandas DataFrame, then we will discuss foe to append one row at a time in it.
Examples of Creating DataFrame in pandas
Create Empty DataFrame
Write pandas script to create empty dataframe
import pandas as pd # Calling DataFrame constructor df = pd.DataFrame() print(df)
In the above script, we have imported pandas library and call default constructor to create an empty dataframe.
Frequently Asked:
Output
Empty DataFrame Columns: [] Index: []
Create DataFrame from list with two columns
import pandas as pd
# initialize list with two columns
data = [['Reema', 10],
['Rekha', 15],
['Jaya', 14]]
# Create the pandas DataFrame
df = pd.DataFrame(data, columns = ['Name', 'Age'])
# print dataframe.
print(df)
In the above script , we have imported pandas library using the import keyword. Then created a list with two columns name and age. To create a DataFrame from a list we have used pandas dataframe constructor with two parameters.
Output
Name Age 0 reema 10 1 Rekha 15 2 jaya 14
Create a Pandas dataframe from a dictionary
import pandas as pd
# Create dictionary with two columns
d = {'rollno': [1, 2],
'Email': ['[email protected]', '[email protected]'] }
# Create the pandas DataFrame
df = pd.DataFrame(data=d)
# print dataframe.
print(df)
In the above script , we have imported pandas library with import keyword, and created a dictionary with two columns and two rows. To create dataFrame from dictionary, pandas dataframe constructor with one argument of dictionary is used.
Output
rollno Email 0 1 [email protected] 1 2 [email protected]
Create Pandas DataFrame from NumPy ndarray
import pandas as pd
import numpy as np
# Create the pandas DataFrame
df = pd.DataFrame(np.array([[10, 'Reema', 'Surat'],
[20, 'Rekha', 'Surat'],
[30, 'Jaya', 'Vapi']]),
columns=['Rollno', 'Name', 'City'])
# print dataframe.
print(df)
Output
Rollno Name City 0 10 Reema Surat 1 20 Rekha Surat 2 30 Jaya Vapi
In the above script, first we have imported two libraries numpy and pandas. Then pandas dataframe is created with three columns rollno, name and city and also three rows.
Create DataFrame from dataclass
import pandas as pd
from dataclasses import make_dataclass
Point = make_dataclass("Point", [("Rollno", int), ("Name", str)])
df = pd.DataFrame( [Point(10, 'Reema'),
Point(20, 'Rekha'),
Point(30, 'Jaya')])
# print dataframe
print(df)
Output
Rollno Name 0 10 Reema 1 20 Rekha 2 30 Jaya
In the above script, make_dataclass method is used to create dataframe from dataclass with two columns , and also add rows with point
Append one row at a time in Pandas DataFrame
We can add a new row in existing DataFrame of Pandas using verious methods. Let’s discuss them one by one,
Append a row using DataFrame.loc method
DataFrame.loc[] method will appned a row in the bottom of the dataframe
Example of append a row in DataFrame using DataFrame.loc method
A script to append a row in dataframe of three columns name, rollno and marks using dataframe.loc method,
import pandas as pd
# Import numpy package
import numpy as np
# Create dataFrame from dictionary
dict = {'Name':['Reema', 'Rekha', 'Jaya', 'susma'],
'Rollno':[1, 2, 3, 4],
'Marks':[83, 99, 84, 76] }
# Create the pandas DataFrame
df = pd.DataFrame(dict)
# print dataframe.
print(df)
# Append a new row in DataFrame
df.loc[len(df.index)] = ['Meena', 5, 93]
print(df)
Output
Name Rollno Marks 0 Reema 1 83 1 Rekha 2 99 2 Jaya 3 84 3 susma 4 76 Name Rollno Marks 0 Reema 1 83 1 Rekha 2 99 2 Jaya 3 84 3 susma 4 76 4 Meena 5 93
In the above script , we have imported two libraries pandas and numpy. To create dataframe, we have created dictionary with three columns name, rollno and marks. To create dataframe from dictionary pandas.DataFrame() method is used. To append new row into already created dataframe dataframe df.loc method is applied with dataframe with length position and new row values.
Append a row to DataFrame using append() method
DataFrame.append() method is use to add a new row in the DataFrame using lists.
A script to create dataframe and append a row using dataframe.append() method is as follows,
import pandas as pd
import numpy as np
# Create dataFrame from dictionary
dict = {'Name':['Reema', 'Rekha', 'Jaya', 'susma'],
'Rollno':[1, 2, 3, 4],
'Marks':[83, 99, 84, 76] }
# Create the pandas DataFrame
df = pd.DataFrame(dict)
# print dataframe.
print(df)
print()
# Append a new row in DataFrame
df2 = { 'Name': 'Meera',
'Rollno': 5,
'Marks': 93}
# Add a row to DataFrame
df = df.append(df2, ignore_index = True)
print(df)
In the above script , first we have imported two libraries pandas and numpy , create dictionary with three columns and four rows , than create dataframe from dictionary
to append a row another dataframe is created and using dataframe.append method import newly created dataframe into existing dataframe
Output
Name Rollno Marks 0 Reema 1 83 1 Rekha 2 99 2 Jaya 3 84 3 susma 4 76 Name Rollno Marks 0 Reema 1 83 1 Rekha 2 99 2 Jaya 3 84 3 susma 4 76 4 Meera 5 93
Summary
In this article of we learned how to create a Pandas Dataframe and append one row at a time. We have discussed what is dataframe in pandas, the syntax of dataframe, how to create a dataframe. What are the ways to append a new row in existing dataframe in pandas, and also explained each methods to append a row with examples.
