How to load a tsv file into a Pandas DataFrame?
Question:
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:Python27libsite-packagespandascoreframe.py", line 318, in __init__
raise PandasError('DataFrame constructor not properly called!')
PandasError: DataFrame constructor not properly called!
Answers:
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).
Use pandas.read_table(filepath). The default separator is tab.
As of 17.0 from_csv is discouraged.
Use pd.read_csv(fpath, sep='t') or pd.read_table(fpath).
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
Try this
df = pd.read_csv("rating-data.tsv",sep='t')
df.head()
You actually need to fix the sep parameter.
df = pd.read_csv('filename.csv', sep='t', header=0)
You can load the tsv file directly into pandas data frame by specifying delimitor and header.
data = pd.read_csv('your_dataset.tsv', delimiter = 't', quoting = 3)
You can use a delimiter to separate data, quoting = 3 helps to clear quotes in datasst
Try this:
import pandas as pd
DataFrame = pd.read_csv("dataset.tsv", sep="t")
use this
import pandas as pd
df = pd.read_fwf('xxxx.tsv')
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:Python27libsite-packagespandascoreframe.py", line 318, in __init__
raise PandasError('DataFrame constructor not properly called!')
PandasError: DataFrame constructor not properly called!
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).
Use pandas.read_table(filepath). The default separator is tab.
As of 17.0 from_csv is discouraged.
Use pd.read_csv(fpath, sep='t') or pd.read_table(fpath).
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
Try this
df = pd.read_csv("rating-data.tsv",sep='t')
df.head()
You actually need to fix the sep parameter.
df = pd.read_csv('filename.csv', sep='t', header=0)
You can load the tsv file directly into pandas data frame by specifying delimitor and header.
data = pd.read_csv('your_dataset.tsv', delimiter = 't', quoting = 3)
You can use a delimiter to separate data, quoting = 3 helps to clear quotes in datasst
Try this:
import pandas as pd
DataFrame = pd.read_csv("dataset.tsv", sep="t")
use this
import pandas as pd
df = pd.read_fwf('xxxx.tsv')