18 个 Jupyter Notebook 小技巧，帮助你快速腾飞

from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity = "all"
from pydataset import data
quakes = data('quakes')
quakes.head()
quakes.tail()

c = get_config()
# Run all nodes interactively
c.InteractiveShell.ast_node_interactivity = "all"

?str.replace()
Docstring:
S.replace(old, new[, count]) -> str
Return a copy of S with all occurrences of substring
old replaced by new.  If the optional argument count is
given, only the first count occurrences are replaced.
Type:      method_descriptor

# This will list all magic commands
%lsmagic
Available line magics:
%alias %alias_magic %autocall %automagic %autosave %bookmark %cat %cd %clear %colors %config %connect_info %cp %debug %dhist %dirs %doctest_mode %ed %edit %env %gui %hist %history %killbgscripts %ldir %less %lf %lk %ll %load %load_ext %loadpy %logoff %logon %logstart %logstate %logstop %ls %lsmagic %lx %macro %magic %man %matplotlib %mkdir %more %mv %notebook %page %pastebin %pdb %pdef %pdoc %pfile %pinfo %pinfo2 %popd %pprint %precision %profile %prun %psearch %psource %pushd %pwd %pycat %pylab %qtconsole %quickref %recall %rehashx %reload_ext %rep %rerun %reset %reset_selective %rm %rmdir %run %save %sc %set_env %store %sx %system %tb %time %timeit %unalias %unload_ext %who %who_ls %whos %xdel %xmode 
Available cell magics:%%! %%HTML %%SVG %%bash %%capture %%debug %%file %%html %%javascript %%js %%latex %%perl %%prun %%pypy %%python %%python2 %%python3 %%ruby %%script %%sh %%svg %%sx %%system %%time %%timeit %%writefile 
Automagic is ON, % prefix IS NOT needed for line magics.

# Running %env without any arguments
# lists all environment variables# The line below sets the environment
# variable
%env OMP_NUM_THREADS%env OMP_NUM_THREADS=4
env: OMP_NUM_THREADS=4

# this will execute and show the output from
# all code cells of the specified notebook
%run ./two-histograms.ipynb

# Before Running
%load ./hello_world.py
# After Running
# %load ./hello_world.py
if __name__ == "__main__":
 print("Hello World!")
Hello World!

data = 'this is the string I want to pass to different notebook'
%store data
del data # This has deleted the variable
Stored 'data' (str)

%store -r data
print(data)
this is the string I want to pass to different notebook

one = "for the money"
two = "for the show"
three = "to get ready now go cat go"
%who str
one three two

%%time
import time
for _ in range(1000):
 time.sleep(0.01) # sleep for 0.01 seconds
CPU times: user 21.5 ms, sys: 14.8 ms, total: 36.3 ms Wall time: 11.6 s

import numpy
%timeit numpy.random.normal(size=100)
The slowest run took 7.29 times longer than the fastest. This could mean that an intermediate result is being cached.
100000 loops, best of 3: 5.5 µs per loop

%%writefile pythoncode.py 
import numpy
def append_if_not_exists(arr, x):
 if x not in arr:
 arr.append(x)def some_useless_slow_function():
 arr = list()
    for i in range(10000):
        x = numpy.random.randint(0, 10000)
    append_if_not_exists(arr, x)
Writing pythoncode.py

%pycat pythoncode.py
import numpy
def append_if_not_exists(arr, x):
 if x not in arr:
 arr.append(x)def some_useless_slow_function():
 arr = list()
 for i in range(10000):
 x = numpy.random.randint(0, 10000)
 append_if_not_exists(arr, x)

%prun some_useless_slow_function()
26324 function calls in 0.556 seconds 
Ordered by: internal time 
ncalls tottime percall cumtime percall filename:lineno(function)
10000 0.527 0.000 0.528 0.000 :2(append_if_not_exists)
10000 0.022 0.000 0.022 0.000 {method 'randint' of 'mtrand.RandomState' objects}
1 0.006 0.006 0.556 0.556 :6(some_useless_slow_function)
6320 0.001 0.000 0.001 0.000 {method 'append' of 'list' objects}
1 0.000 0.000 0.556 0.556 :1()
1 0.000 0.000 0.556 0.556 {built-in method exec}
1 0.000 0.000 0.000 0.000 {method 'disable' of '_lsprof.Profiler' objects}

%pdb 
def pick_and_take():
 picked = numpy.random.randint(0, 1000)
 raise NotImplementedError()
pick_and_take()
Automatic pdb calling has been turned ON
--------------------------------------------------------------------
NotImplementedError Traceback (most recent call last)
in ()
5 raise NotImplementedError()
6
----> 7 pick_and_take()
in pick_and_take()
3 def pick_and_take():
4 picked = numpy.random.randint(0, 1000)
----> 5 raise NotImplementedError()
6
7 pick_and_take()
NotImplementedError:
> (5)pick_and_take()
3 def pick_and_take():
4 picked = numpy.random.randint(0, 1000)
----> 5 raise NotImplementedError()
6
7 pick_and_take()
ipdb>

!ls *.csv
nba_2016.csv titanic.csv pixar_movies.csv whitehouse_employees.csv

!pip install numpy !pip list | grep pandas
Requirement already satisfied (use --upgrade to upgrade): numpy in /Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages pandas (0.18.1)

$P(A mid B) = frac{P(B mid A)P(A)}{P(B)}$

%%bash
for i in {1..5}
do echo "i is $i"
done
i is 1
i is 2
i is 3
i is 4
i is 5

pip install rpy2

%load_ext rpy2.ipython
%R require(ggplot2)
array([1], dtype=int32)
import pandas as pd df = pd.DataFrame({
'Letter': ['a', 'a', 'a', 'b', 'b', 'b', 'c', 'c', 'c'],
'X': [4, 3, 5, 2, 1, 7, 7, 5, 9],
'Y': [0, 4, 3, 6, 7, 10, 11, 9, 13],
'Z': [1, 2, 3, 1, 2, 3, 1, 2, 3]
})
%%R -i df ggplot(data = df) + geom_point(aes(x = X, y= Y, color = Letter, size = Z))