I tried several times to import CSV file into python 2.7.15 but it fail. Please suggest how to import CSV in Python. Thank you

To read a CSV file as a pandas DataFrame, you'll need to use pd.read_csv, which has sep=',' as the default.. But this isn't where the story ends; data exists in many different formats and is stored in different ways so you will often need to pass additional parameters to read_csv to ensure your data is read in properly.

Apr 19, 2012 · Another common trap with windows paths is that using backslashes escape characters, so you must escape your backslashes ("some\\file") - an ugly option, use raw strings (r"some\file"), use forward slashes (Python will actually handle this automatically), or - the best option, pass your path as arguments to the aforementioned os.path.join().

Oct 7, 2017 · Assuming the CSV file is delimited with commas, the simplest way using the csv module in Python 3 would probably be:

Nov 10, 2021 · I have an implementation that works using Python's csv module, but apparently I am not supposed to use any ...

Sep 1, 2015 · Above is my code. So the requirement is to load data from a .csv file and into a list of tuples. The data in the file is something like: - apple 23.2 24.3 25.6 - banana 22.1 20.0 19.9 Withing each tuple in the list it has to be (word, listoffloats) so the list would look like:

May 28, 2014 · So far, your code and the answers use the Python 2 way of opening the CSV file. The things has changed in Python 3. As shengy wrote, the CSV file is just a text file, and the csv module gets the elements as strings. Strings in Python 3 are unicode strings.

Mar 27, 2021 · Move the file.csv to the same folder as the python script or Jupyter Notebook and then simply use pd.read_csv("file.csv", sep = ";"). The URL which you shared redirects to a page but doesn't download the csv file directly. If you have the …

Indices in read_csv refer to line/row numbers in your csv file (the first line has the index 0). You have the following options to skip rows: You have the following options to skip rows: from io import StringIO csv = \ """col1,col2 1,a 2,b 3,c 4,d """ pd.read_csv(StringIO(csv)) # Output: col1 col2 # index 0 0 1 a # index 1 1 2 b # index 2 2 3 c ...

Pandas is pretty good at dealing with data. Here is one example how to use it: import pandas as pd # Read the CSV into a pandas data frame (df) # With a df you can do many things # most important: visualize data with Seaborn df = pd.read_csv('filename.csv', delimiter=',') # Or export it in many ways, e.g. a list of tuples tuples = [tuple(x) for x …