from_string¶

In [14]:

import pandas as pd
import numpy as np
import io

def from_string(_str, **kwargs):
    # http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.from_csv.html
    return pd.DataFrame.from_csv(io.StringIO(_str), **kwargs)

_csv = """a,b,c
1,2,3
4,5,6
"""

In [4]:

from_string(_csv)

Out[4]:

	b	c
a
1	2	3
4	5	6

In [5]:

from_string(_csv, index_col=None)

Out[5]:

	a	b	c
0	1	2	3
1	4	5	6

In [6]:

from_string(_csv[1:])

Out[6]:

	b	c
1	2	3
4	5	6

In [7]:

pd.read_csv(io.StringIO(_csv))

Out[7]:

	a	b	c
0	1	2	3
1	4	5	6

In [9]:

import pyperclip

def from_clipboad(**kwargs):
    return from_string(pyperclip.paste(), **kwargs)

In [11]:

pyperclip.copy(_csv)
from_clipboad(index_col=None)

Out[11]:

	a	b	c
0	1	2	3
1	4	5	6

In [12]:

pyperclip.copy(_csv)
pd.read_clipboard(sep=",")

Out[12]:

	a	b	c
0	1	2	3
1	4	5	6

In [15]:

import string

df_wide = pd.DataFrame(
    np.random.random_integers(1, size=(1, len(string.ascii_letters))),
    columns=list(string.ascii_letters))

with pd.option_context('display.max_columns', 10):
    print(pd.options.display.max_columns)
    print(df_wide)

print(pd.options.display.max_columns)
print(df_wide)

10
   a  b  c  d  e ...  V  W  X  Y  Z
0  1  1  1  1  1 ...  1  1  1  1  1

[1 rows x 52 columns]
20
   a  b  c  d  e  f  g  h  i  j ...  Q  R  S  T  U  V  W  X  Y  Z
0  1  1  1  1  1  1  1  1  1  1 ...  1  1  1  1  1  1  1  1  1  1

[1 rows x 52 columns]

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