In This Article, You Will Learn About Python Pandas DataFrame
Python Pandas DataFrame – Before moving ahead, let’s know about Python Introduction
Table of Contents
DataFrame
A Pandas DataFrame is a 2D data structure, similar to an array with two dimensions, or a table, with columns and rows.
Example – Creating a DataFrame from two Series.
import pandas as pd
info = {
"Name": ["A", "B", "C"],
"Score": [90, 89, 98]
}
data = pd.DataFrame(info)
print(data)
As shown clearly, it returned 2D data in tabular form.
Locate Row
You can see that the DataFrame functions like a table that has columns and rows. Pandas utilize their loc attribute to return one or more specific row(s).
Example – Locating the 2d row from 2D data.
import pandas as pd
info = {
"Name": ["A", "B", "C"],
"Score": [90, 89, 98]
}
data = pd.DataFrame(info)
print(data.loc[2])
As shown above, it returned the specified data i.e., 2nd row’s data after using default row’s name as index argument.
Example – Locating the multiple rows.
import pandas as pd
info = {
"Name": ["A", "B", "C"],
"Score": [90, 89, 98]
}
data = pd.DataFrame(info)
print(data.loc[[0,2]])
As a result, it returned specified data within the range.
Note: Using the parenthesis — [ ] we can get the data in DataFrame.
Name Indexes
By using index argument, we can put name to our own indexes.
Example – Creating a list of name to give name to rows.
import pandas as pd
info = {
"Name": ["A", "B", "C"],
"Score": [90, 89, 98]
}
data = pd.DataFrame(info, index=["Class-X", "Class-XI", "Class-XII"])
print(data)
It has been noticed, it returned each row has been defined with their row name.
Locate Named Indexes
Using the named index of the loc attribute to retrieve the specified row(s).
Example – Locating the 2d row from 2D data.
import pandas as pd
info = {
"Name": ["A", "B", "C"],
"Score": [90, 89, 98]
}
data = pd.DataFrame(info)
print(data.loc["Class-XII"])
As shown above, it returned specified data (2D row) from 2D data by using row name as index argument.
Load Files
If your data is stored in a file, then Pandas can load it to DataFrame.
Example – Loading a file CSV file into a DataFrame.
import pandas as pd
file = pd.read_csv('myfile.csv')
print(file)
As shown above, it loaded given file with the help of Pandas read_csv function.
If you find anything incorrect in the above-discussed topic and have any further questions, please comment below.
