Actual behaviour. Import Pandas: import pandas as pd Code #1 : read_csv is an important pandas function to read csv files and do operations on it. If this doesn't help, just print out your sys.stdin to check if you properly pass the text. The filepath_or_buffer argument is missing completely. pandas.read_csv(filepath_or_buffer, sep=', ', delimiter=None, header='infer', names=None, index_col=None, ....) It reads the content of a csv file at given path, then loads the content to a Dataframe and returns that. Parameter hints. Teams. Using delimiter='\t' should also work, unless the tabs are expanded (replaced by spaces). If this doesn't help, just print out your sys.stdin to check if you properly pass the text. Edit: I just saw that you use For file URLs, a host is expected. --> 445 parser = TextFileReader(filepath_or_buffer, **kwds) 446 447 if … read_csv. pandas.read_csv(filepath_or_buffer) Ad. c:\program files\python36\lib\site-packages\pandas\io\parsers.py in _read(filepath_or_buffer, kwds) 443 444 # Create the parser. Parameters filepath_or_buffer str, path object or file-like object. Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Python Pandas read_csv: Load Data from CSV Files, Pandas DataFrames is an excel like data structure with labeled axes (rows and columns). Using delimiter='\t' should also work, unless the tabs are expanded (replaced by spaces). The string can be a URL hosted on a server or a local file hosted on the user’s computer. The tooltip/parameter hints for pandas.read_csv should have as first argument of the function filepath_or_buffer as in the documentation. pandas.read_csv ¶ pandas.read_csv ... filepath_or_buffer: str, pathlib.Path, py._path.local.LocalPath or any object with a read() method (such as a file handle or StringIO) The string could be a URL. Valid URL schemes include http, ftp, s3, and file. Here is an example of pandas DataFrame that we read_csv. The first argument of read_csv in the tooltip is sep as shown below. Hover. It uses comma (,) as default delimiter or separator while parsing a file. Any valid string path is acceptable. The string could be a URL. pandas.read_fwf¶ pandas.read_fwf (filepath_or_buffer, colspecs = 'infer', widths = None, infer_nrows = 100, ** kwds) [source] ¶ Read a table of fixed-width formatted lines into DataFrame. The basic read_csv function can be used on any filepath or URL that points to a .csv file. … Also supports optionally iterating or breaking of the file into chunks. Edit: I just saw that you use So i tried reading all the csv files from a folder and then concatenate them to create a big csv(structure of all the files was same), save it and read it again. pandas.read_csv(filepath_or_buffer, delim_whitespace=True). pandas.read_csv(filepath_or_buffer, delim_whitespace=True). import pandas as pd from sklearn.tree import DecisionTreeClassifier books_data = pd.read_csv(r'C:\Users\ME\Desktop\buc.csv') but there are the same erors What should I do? Here we’ll do a deep dive into the read_csv function in Pandas to help you understand everything it can do and what to check if you get errors. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. 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