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Merged
merged 4 commits into from
Dec 9, 2018
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DOC: update usage of randn in io.rst #24154

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fd7c683
replace randn with np.random.randn
charlesdong1991 Dec 7, 2018
f7826ee
fix linting error
charlesdong1991 Dec 8, 2018
9487ef8
resubmit pr
charlesdong1991 Dec 8, 2018
6d0622c
fix linting error
charlesdong1991 Dec 8, 2018
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40 changes: 20 additions & 20 deletions doc/source/io.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,6 @@
from pandas.compat import StringIO, BytesIO


randn = np.random.randn
np.set_printoptions(precision=4, suppress=True)
plt.close('all')
pd.options.display.max_rows = 15
Expand Down Expand Up @@ -1767,7 +1766,7 @@ Note ``NaN``'s, ``NaT``'s and ``None`` will be converted to ``null`` and ``datet

.. ipython:: python

dfj = pd.DataFrame(randn(5, 2), columns=list('AB'))
dfj = pd.DataFrame(np.random.randn(5, 2), columns=list('AB'))
json = dfj.to_json()
json

Expand Down Expand Up @@ -1842,7 +1841,7 @@ Writing in ISO date format:

.. ipython:: python

dfd = pd.DataFrame(randn(5, 2), columns=list('AB'))
dfd = pd.DataFrame(np.random.randn(5, 2), columns=list('AB'))
dfd['date'] = pd.Timestamp('20130101')
dfd = dfd.sort_index(1, ascending=False)
json = dfd.to_json(date_format='iso')
Expand Down Expand Up @@ -2482,7 +2481,7 @@ Read in pandas ``to_html`` output (with some loss of floating point precision):

.. code-block:: python

df = pd.DataFrame(randn(2, 2))
df = pd.DataFrame(np.random.randn(2, 2))
s = df.to_html(float_format='{0:.40g}'.format)
dfin = pd.read_html(s, index_col=0)

Expand Down Expand Up @@ -2535,7 +2534,7 @@ in the method ``to_string`` described above.

.. ipython:: python

df = pd.DataFrame(randn(2, 2))
df = pd.DataFrame(np.random.randn(2, 2))
df
print(df.to_html()) # raw html

Expand Down Expand Up @@ -2611,7 +2610,7 @@ Finally, the ``escape`` argument allows you to control whether the

.. ipython:: python

df = pd.DataFrame({'a': list('&<>'), 'b': randn(3)})
df = pd.DataFrame({'a': list('&<>'), 'b': np.random.randn(3)})


.. ipython:: python
Expand Down Expand Up @@ -3187,7 +3186,7 @@ applications (CTRL-V on many operating systems). Here we illustrate writing a

.. ipython:: python

df = pd.DataFrame(randn(5, 3))
df = pd.DataFrame(np.random.randn(5, 3))
df
df.to_clipboard()
pd.read_clipboard()
Expand Down Expand Up @@ -3414,10 +3413,10 @@ dict:
.. ipython:: python

index = pd.date_range('1/1/2000', periods=8)
s = pd.Series(randn(5), index=['a', 'b', 'c', 'd', 'e'])
df = pd.DataFrame(randn(8, 3), index=index,
s = pd.Series(np.random.randn(5), index=['a', 'b', 'c', 'd', 'e'])
df = pd.DataFrame(np.random.randn(8, 3), index=index,
columns=['A', 'B', 'C'])
wp = pd.Panel(randn(2, 5, 4), items=['Item1', 'Item2'],
wp = pd.Panel(np.random.randn(2, 5, 4), items=['Item1', 'Item2'],
major_axis=pd.date_range('1/1/2000', periods=5),
minor_axis=['A', 'B', 'C', 'D'])

Expand Down Expand Up @@ -3563,7 +3562,7 @@ This format is specified by default when using ``put`` or ``to_hdf`` or by ``for

.. code-block:: python

>>> pd.DataFrame(randn(10, 2)).to_hdf('test_fixed.h5', 'df')
>>> pd.DataFrame(np.random.randn(10, 2)).to_hdf('test_fixed.h5', 'df')
>>> pd.read_hdf('test_fixed.h5', 'df', where='index>5')
TypeError: cannot pass a where specification when reading a fixed format.
this store must be selected in its entirety
Expand Down Expand Up @@ -3699,9 +3698,9 @@ defaults to `nan`.

.. ipython:: python

df_mixed = pd.DataFrame({'A': randn(8),
'B': randn(8),
'C': np.array(randn(8), dtype='float32'),
df_mixed = pd.DataFrame({'A': np.random.randn(8),
'B': np.random.randn(8),
'C': np.array(np.random.randn(8), dtype='float32'),
'string': 'string',
'int': 1,
'bool': True,
Expand Down Expand Up @@ -3841,7 +3840,7 @@ Here are some examples:

.. ipython:: python

dfq = pd.DataFrame(randn(10, 4), columns=list('ABCD'),
dfq = pd.DataFrame(np.random.randn(10, 4), columns=list('ABCD'),
index=pd.date_range('20130101', periods=10))
store.append('dfq', dfq, format='table', data_columns=True)

Expand Down Expand Up @@ -3946,8 +3945,8 @@ Oftentimes when appending large amounts of data to a store, it is useful to turn

.. ipython:: python

df_1 = pd.DataFrame(randn(10, 2), columns=list('AB'))
df_2 = pd.DataFrame(randn(10, 2), columns=list('AB'))
df_1 = pd.DataFrame(np.random.randn(10, 2), columns=list('AB'))
df_2 = pd.DataFrame(np.random.randn(10, 2), columns=list('AB'))

st = pd.HDFStore('appends.h5', mode='w')
st.append('df', df_1, data_columns=['B'], index=False)
Expand Down Expand Up @@ -4151,7 +4150,8 @@ results.

.. ipython:: python

df_mt = pd.DataFrame(randn(8, 6), index=pd.date_range('1/1/2000', periods=8),
df_mt = pd.DataFrame(np.random.randn(8, 6),
index=pd.date_range('1/1/2000', periods=8),
columns=['A', 'B', 'C', 'D', 'E', 'F'])
df_mt['foo'] = 'bar'
df_mt.loc[df_mt.index[1], ('A', 'B')] = np.nan
Expand Down Expand Up @@ -5181,7 +5181,7 @@ into a .dta file. The format version of this file is always 115 (Stata 12).

.. ipython:: python

df = pd.DataFrame(randn(10, 2), columns=list('AB'))
df = pd.DataFrame(np.random.randn(10, 2), columns=list('AB'))
df.to_stata('stata.dta')

*Stata* data files have limited data type support; only strings with
Expand Down Expand Up @@ -5405,7 +5405,7 @@ ignored.
.. code-block:: ipython

In [1]: sz = 1000000
In [2]: df = pd.DataFrame({'A': randn(sz), 'B': [1] * sz})
In [2]: df = pd.DataFrame({'A': np.random.randn(sz), 'B': [1] * sz})

In [3]: df.info()
<class 'pandas.core.frame.DataFrame'>
Expand Down