DataFrames
If one column is not enough and you want to store data like in a spreadsheet, then you most likely will use DataFrames.
What is DataFrame?
Pandas DataFrame is a two-dimensional, size-mutable, tabular data, that may consist of values of different types. You can think of dataframes as tables.
There are several ways of DataFrame creating. They are all based on the use of different parameters within pd.DataFrame() method. First, you can pass list of lists - this will populate the table just like nested lists look like.
123456# Importing library import pandas as pd # Create DataFrame df = pd.DataFrame([[1, 2, 3], [4, 5, 6]]) print(df)
Also you can create a DataFrame with predefined column's names. To it, pass a dictionary as the parameter. Keys of this dictionary will be the column's names and dictionary values will be respective column' values.
Dictionary is an ordered collection, that stores data in
key:valueformat. To create a dictionary, use curly brackets, and passkey:valuepairs. For instance,d = {'key1': 'value1', 'key2': 'value2'}. Dictonary values can be either strings, or numbers, or lists, or arrays.
123456# Importing library import pandas as pd # Create DataFrame df = pd.DataFrame({'column1': [1, 2, 3], 'column2': [4, 5, 6]}) print(df)
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If one column is not enough and you want to store data like in a spreadsheet, then you most likely will use DataFrames.
What is DataFrame?
Pandas DataFrame is a two-dimensional, size-mutable, tabular data, that may consist of values of different types. You can think of dataframes as tables.
There are several ways of DataFrame creating. They are all based on the use of different parameters within pd.DataFrame() method. First, you can pass list of lists - this will populate the table just like nested lists look like.
123456# Importing library import pandas as pd # Create DataFrame df = pd.DataFrame([[1, 2, 3], [4, 5, 6]]) print(df)
Also you can create a DataFrame with predefined column's names. To it, pass a dictionary as the parameter. Keys of this dictionary will be the column's names and dictionary values will be respective column' values.
Dictionary is an ordered collection, that stores data in
key:valueformat. To create a dictionary, use curly brackets, and passkey:valuepairs. For instance,d = {'key1': 'value1', 'key2': 'value2'}. Dictonary values can be either strings, or numbers, or lists, or arrays.
123456# Importing library import pandas as pd # Create DataFrame df = pd.DataFrame({'column1': [1, 2, 3], 'column2': [4, 5, 6]}) print(df)
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