Pandas is the most popular open-source library in the Python programming language and pandas is widely used for data science/data analysis and machine learning applications.
Pandas is a Python library used for working with data sets. It has functions for analyzing, cleaning, exploring, and manipulating data.
The name "Pandas" has a reference to both "Panel Data", and "Python Data Analysis".
pip install pandasPandas Series:
A Pandas Series is like a row in a table. It is a one-dimensional array holding data of any type.
product = [1, 7, 2]
product = pd.Series(product)
print(product)
type(product) # pandas.core.series.Seriesproduct = [1, 7, 2]
index = ["x", "y", "z"]
product = pd.Series(product,index=index)
print(product)
calories = {"day1": 420, "day2": 380, "day3": 390}
myvar = pd.Series(calories)
print(myvar)
DataFrames:
A Pandas DataFrame is a 2 dimensional data structure, like a 2 dimensional array, or a table with rows and columns.
Series is like a column, a DataFrame is the whole table.
data = {
"calories": [420, 380, 390],
"duration": [50, 40, 45]
}
#load data into a DataFrame object:
df = pd.DataFrame(data, index = ["day1", "day2", "day3"])
print(df) 
Read CSV Files:
data = {
"Duration":{
"0":60,
"1":60,
"2":60,
"3":45,
"4":45,
"5":60
},
"Pulse":{
"0":110,
"1":117,
"2":103,
"3":109,
"4":117,
"5":102
},
"Maxpulse":{
"0":130,
"1":145,
"2":135,
"3":175,
"4":148,
"5":127
},
"Calories":{
"0":409,
"1":479,
"2":340,
"3":282,
"4":406,
"5":300
}
}
df = pd.DataFrame(data)
print(df) 
