As we know that data comes in all shapes and sizes. They often come from various sources having different formats. We have some data present in string format, and discuss ways to load that data into Pandas Dataframe.
Method 1: Create Pandas DataFrame from a string using StringIO()
One way to achieve this is by using the StringIO() function. It will act as a wrapper and it will help us to read the data using the pd.read_csv() function.
Python3
# importing pandas as pd import pandas as pd # import the StrinIO function # from io module from io import StringIO # wrap the string data in StringIO function StringData = StringIO( """Date;Event;Cost 10/2/2011;Music;10000 11/2/2011;Poetry;12000 12/2/2011;Theatre;5000 13/2/2011;Comedy;8000 """ ) # let's read the data using the Pandas # read_csv() function df = pd.read_csv(StringData, sep = ";" ) # Print the dataframe print (df) |
Output :
Date Event Cost
0 10/2/2011 Music 10000
1 11/2/2011 Poetry 12000
2 12/2/2011 Theatre 5000
3 13/2/2011 Comedy 8000
Method 2: Create Pandas DataFrame from a string using Pandas read_clipboard()
Another fantastic approach is to use the Pandas pd.read_clipboard() function. This is what it looks like after we copy the data to the clipboard. Now we will use Pandas pd.read_clipboard() function to read the data into a DataFrame.
Python3
# importing pandas as pd import pandas as pd # This is our string data StringData = """Date;Event;Cost 10/2/2011;Music;10000 11/2/2011;Poetry;12000 12/2/2011;Theatre;5000 13/2/2011;Comedy;8000 """ # Read data df = pd.read_clipboard(sep = ';' ) # Print the DataFrame print (df) |
Output :
Date Event Cost
0 10/2/2011 Music 10000
1 11/2/2011 Poetry 12000
2 12/2/2011 Theatre 5000
3 13/2/2011 Comedy 8000