In the package overview, they talk about the two primary data structures of pandas: series and a data

frame.

• A data frame is kind of the equivalent of your whole table here. So every single sheet inside an Excel file or inside a Google sheet file would be considered a data frame in pandas.
• The series is the other super important concept in pandas. And the series is basically equivalent to a list. It's kind of like a single column in your table.

Read CSV file via pandas

import pandas

data = pandas.read_csv("weather_data.csv")
print(data)
print(data["temp"])

data_dict = data.to_dict()
temp_list = data["temp"].to_list()

Different use case

import pandas
data = pandas.read_csv("weather_data.csv")

#Get the average of temp column
#1 
temp_list = data["temp"].to_list()
average = sum(temp_list) / len(temp_list)
#2
print(data["temp"].mean())
#3
import statistics
print(statistics.mean(temp_list))

#Get the max number of temp
data["temp"].max()

#Get data in Columns
data["condition"]
data.condition

#Calcualte the data
monday = data[data.day == "Monday"]
monday_temp = int(monday.temp) * 9/5 + 32
print(monday_temp)

Create a dataframe from scratch

import pandas

data_dict = {
    "students": ["Amy", "James", "Angela"],
    "score": [76, 56, 65]
}

data = pandas.DataFrame(data_dict)
data.to_csv("new_data.csv")

students  score
0      Amy     76
1    James     56
2   Angela     65