Python Pandas DataFrames Made Simple

A Pandas DataFrame is a 2 dimensional data structure, like a 2 dimensional array, or a table with rows and columns. A Pandas DataFrame has three main components: the data, rows, and columns.

Columns and Rows :

Columns : Represent different variables or features. Each column has a name (column label).

Rows : Contain the actual data entries. Each row has a unique index.

Example

Create a simple Pandas DataFrame :

import pandas as pd

data = {
  “calories”: [420, 380, 390],
  “duration”: [50, 40, 45]
}

#load data into a DataFrame object:
df = pd.DataFrame(data)

print(df)

Result :

Locate Row :

Pandas use the loc attribute to return one or more specified row(s)

#returns to the row index:
print(df.loc[0])

Column Selection :

# Returns the ‘calories’ column
df[ ’calories’ ]

Manipulating Data :

· Adding a Column:

df[‘Salary’] = [60000, 80000, 75000]

· Filtering Data:

# Return rows where ‘calories’ is greater than 30

df[df[‘calories‘] > 30]