How to load a tsv file into a Pandas DataFrame?

Question

I'm new to python and pandas. I'm trying to get a tsv file loaded into a pandas DataFrame .

This is what I'm trying and the error I'm getting:

>>> df1 = DataFrame(csv.reader(open('c:/~/trainSetRel3.txt'), delimiter='\t'))

Traceback (most recent call last):
  File "<pyshell#28>", line 1, in <module>
    df1 = DataFrame(csv.reader(open('c:/~/trainSetRel3.txt'), delimiter='\t'))
  File "C:\Python27\lib\site-packages\pandas\core\frame.py", line 318, in __init__
    raise PandasError('DataFrame constructor not properly called!')
PandasError: DataFrame constructor not properly called!

Answer 1

The .read_csv function does what you want:

pd.read_csv('c:/~/trainSetRel3.txt', sep='\t')

If you have a header, you can pass header=0 .

pd.read_csv('c:/~/trainSetRel3.txt', sep='\t', header=0)

Note : Prior 17.0, pd.DataFrame.from_csv was used (it is now deprecated and the .from_csv documentation link redirects to the page for pd.read_csv ).

Answer 2

As of 17.0 from_csv is discouraged.

Use pd.read_csv(fpath, sep='\t') or pd.read_table(fpath) .

Answer 3

Use pandas.read_table(filepath) . The default separator is tab.

Answer 4

Try this

df = pd.read_csv("rating-data.tsv",sep='\t')
df.head()

You actually need to fix the sep parameter.

Answer 5

open file, save as .csv and then apply

df = pd.read_csv('apps.csv', sep='\t')

for any other format also, just change the sep tag

Answer 6

data = pd.read_csv('your_dataset.tsv', delimiter = '\t', quoting = 3)

您可以使用分隔符来分隔数据，quoting = 3 有助于清除 datasst 中的引号

Answer 7

df = pd.read_csv('filename.csv', sep='\t', header=0)

您可以通过指定分隔符和标头将 tsv 文件直接加载到 pandas 数据框中。

Answer 8

Try this:

import pandas as pd
DataFrame = pd.read_csv("dataset.tsv", sep="\t")

Answer 9

use this

import pandas as pd
df = pd.read_fwf('xxxx.tsv')