This is a question from someone who tries to answer questions about pandas dataframes. Consider a question with a given dataset which is just the visualization (not the actual code), for example:
numbers letters dates all
0 1 a 20-10-2020 NaN
1 2 b 21-10-2020 b
2 3 c 20-11-2020 4
3 4 d 20-10-2021 20-10-2020
4 5 e 10-10-2020 3.14
Is it possible to quickly import this in python as a dataframe or as a dictionary? So far I copied the given text and transformed it to a dataframe by making strings (adding '') and so on.
I think there are two 'solutions' for this:
read_clipboardYou can use pd.read_clipboard() optionally with a separator (e.g. pd.read_clipboard('\s\s+') if you have datetime strings or spaces in column names and columns are separated by at least two spaces):
pd.read_clipboard()Note that this doesn't work well on all platforms.
read_csv + io.StringIOFor more complex formats, combine read_csv combined with io.StringIO:
data = '''
numbers letters dates all
0 1 a 20-10-2020 NaN
1 2 b 21-10-2020 b
2 3 c 20-11-2020 4
3 4 d 20-10-2021 20-10-2020
4 5 e 10-10-2020 3.14
'''
import io
df = pd.read_csv(io.StringIO(data), sep='\s+')
df
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