You can use the following basic syntax to create a pandas DataFrame from a string:
import pandas as pd import io df = pd.read_csv(io.StringIO(string_data), sep=",")
This particular syntax creates a pandas DataFrame using the values contained in the string called string_data.
The following examples show how to use this syntax in practice.
Example 1: Create DataFrame from String with Comma Separators
The following code shows how to create a pandas DataFrame from a string in which the values in the string are separated by commas:
import pandas as pd import io #define string string_data="""points, assists, rebounds 5, 15, 22 7, 12, 9 4, 3, 18 2, 5, 10 3, 11, 5 """ #create pandas DataFrame from string df = pd.read_csv(io.StringIO(string_data), sep=",") #view DataFrame print(df) points assists rebounds 0 5 15 22 1 7 12 9 2 4 3 18 3 2 5 10 4 3 11 5
The result is a pandas DataFrame with five rows and three columns.
Example 2: Create DataFrame from String with Semicolon Separators
The following code shows how to create a pandas DataFrame from a string in which the values in the string are separated by semicolons:
import pandas as pd import io #define string string_data="""points;assists;rebounds 5;15;22 7;12;9 4;3;18 2;5;10 3;11;5 """ #create pandas DataFrame from string df = pd.read_csv(io.StringIO(string_data), sep=";") #view DataFrame print(df) points assists rebounds 0 5 15 22 1 7 12 9 2 4 3 18 3 2 5 10 4 3 11 5
The result is a pandas DataFrame with five rows and three columns.
If you have a string with a different separator, simply use the sep argument within the read_csv() function to specify the separator.
Additional Resources
The following tutorials explain how to perform other common tasks in pandas:
How to Convert Pandas DataFrame Columns to Strings
How to Convert Timestamp to Datetime in Pandas
How to Convert Datetime to Date in Pandas