Read lists into columns of pandas DataFrame

Read lists into columns of pandas DataFrame

To read lists into columns of a pandas DataFrame, you can create a DataFrame with each list representing a column. You can use the pd.DataFrame() constructor to achieve this. Here's an example:

import pandas as pd # Example lists list1 = [1, 2, 3] list2 = ['A', 'B', 'C'] list3 = [10.1, 20.2, 30.3] # Create a DataFrame with lists as columns df = pd.DataFrame({ 'Column1': list1, 'Column2': list2, 'Column3': list3 }) print(df)

Output:

 Column1 Column2 Column3 0 1 A 10.1 1 2 B 20.2 2 3 C 30.3

In this example, we used the pd.DataFrame() constructor and provided a dictionary where the keys are the column names, and the values are the corresponding lists. The DataFrame is created with each list becoming a separate column.

You can adjust the column names and the number of lists you want to include based on your data.

Examples

  1. Creating a Pandas DataFrame from Lists as Columns

    • This snippet demonstrates how to create a Pandas DataFrame by directly assigning lists to columns.
    !pip install pandas 
    import pandas as pd # Create a DataFrame from lists data = { "names": ["Alice", "Bob", "Charlie"], "ages": [25, 30, 35], "city": ["New York", "Los Angeles", "Chicago"] } df = pd.DataFrame(data) print("DataFrame:", df)

  2. Reading Lists into Columns from a CSV File

    • This snippet shows how to read CSV data into a DataFrame where certain columns contain lists.
    !pip install pandas 
    import pandas as pd # CSV data with lists csv_data = "names,ages,city\nAlice,25,New York\nBob,30,Los Angeles\nCharlie,35,Chicago" df = pd.read_csv(pd.io.common.StringIO(csv_data)) print("DataFrame:", df)

  3. Reading JSON Data with Lists into a DataFrame

    • This snippet demonstrates how to read JSON data where some fields contain lists, creating a Pandas DataFrame.
    !pip install pandas 
    import pandas as pd import json # JSON data with lists json_data = '{"names": ["Alice", "Bob"], "ages": [25, 30], "city": ["New York", "Los Angeles"]}' data = json.loads(json_data) df = pd.DataFrame(data) print("DataFrame:", df)

  4. Converting Nested Lists into Columns

    • This snippet demonstrates how to handle nested lists and convert them into DataFrame columns.
    !pip install pandas 
    import pandas as pd # Nested lists nested_lists = { "data": [ {"name": "Alice", "scores": [85, 90, 78]}, {"name": "Bob", "scores": [82, 88, 91]} ] } df = pd.json_normalize(nested_lists["data"]) print("DataFrame:", df)

  5. Reading Lists from a File into DataFrame Columns

    • This snippet shows how to read data from a file where some lines contain lists, creating a DataFrame.
    !pip install pandas 
    import pandas as pd # Create a DataFrame from a text file with lists file_content = "Alice,25,New York, 85, 90, 78\nBob,30,Los Angeles, 82, 88, 91" df = pd.read_csv(pd.io.common.StringIO(file_content), header=None) df.columns = ["Name", "Age", "City", "Score1", "Score2", "Score3"] print("DataFrame:", df)

  6. Converting List of Dictionaries into a DataFrame

    • This snippet demonstrates how to convert a list of dictionaries into a DataFrame with columns.
    !pip install pandas 
    import pandas as pd # List of dictionaries list_of_dicts = [ {"name": "Alice", "age": 25, "city": "New York"}, {"name": "Bob", "age": 30, "city": "Los Angeles"} ] df = pd.DataFrame(list_of_dicts) print("DataFrame:", df)

  7. Creating a DataFrame from Multiple Lists

    • This snippet demonstrates how to create a DataFrame from multiple lists, each becoming a column.
    !pip install pandas 
    import pandas as pd # Lists to be converted into DataFrame columns names = ["Alice", "Bob", "Charlie"] ages = [25, 30, 35] cities = ["New York", "Los Angeles", "Chicago"] df = pd.DataFrame({ "Name": names, "Age": ages, "City": cities }) print("DataFrame:", df)

  8. Reading Lists from Excel into DataFrame Columns

    • This snippet demonstrates how to read Excel data where some columns contain lists.
    !pip install pandas 
    import pandas as pd # Read Excel data into DataFrame with lists in columns excel_file_path = "data.xlsx" df = pd.read_excel(excel_file_path, sheet_name=0) print("DataFrame from Excel:", df)

  9. Handling Lists within Pandas Series

    • This snippet shows how to handle Pandas Series where some elements are lists, and convert them to DataFrame columns.
    !pip install pandas 
    import pandas as pd # Pandas Series containing lists series_with_lists = pd.Series([ ["Alice", "Bob", "Charlie"], [25, 30, 35], ["New York", "Los Angeles", "Chicago"] ]) # Convert Series into DataFrame df = pd.DataFrame(series_with_lists.tolist()).T # Transpose to get correct orientation df.columns = ["Name", "Age", "City"] print("DataFrame:", df)

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