ipython

Use IPython magic functions in ipdb shell

由 不羁的心 提交于 2020-01-11 15:25:58
问题 When debugging Python script using ipdb my_script.py , I want to use IPython magic functions like %paste , %cd in ipdb debug session shell. Is is possible and how? 回答1: According to the ipdb Github repo magic IPython functions are not available. Fortunately, the IPython debugger provides a couple of clues of how to get this functionality without launching a separate IPython shell. Here is what I did to run %cpaste : ipdb> from IPython import get_ipython ipdb> shell = get_ipython() ipdb> shell

Assigning dtype value using array.dtype = <data type> in NumPy arrays gives ambiguous results

由 我怕爱的太早我们不能终老 提交于 2020-01-11 10:21:55
问题 I am new to programming and numpy... While reading tutorials and experimenting on jupyter-notebook... I thought of converting dtype of a numpy array as follows: import numpy as np c = np.random.rand(4)*10 print c #Output1: [ 0.12757225 5.48992242 7.63139022 2.92746857] c.dtype = int print c #Output2: [4593764294844833304 4617867121563982285 4620278199966380988 4613774491979221856] I know the proper way of changing is: c = c.astype(int) But I want to the reason behind those ambiguous numbers

Assigning dtype value using array.dtype = <data type> in NumPy arrays gives ambiguous results

由 落花浮王杯 提交于 2020-01-11 10:21:51
问题 I am new to programming and numpy... While reading tutorials and experimenting on jupyter-notebook... I thought of converting dtype of a numpy array as follows: import numpy as np c = np.random.rand(4)*10 print c #Output1: [ 0.12757225 5.48992242 7.63139022 2.92746857] c.dtype = int print c #Output2: [4593764294844833304 4617867121563982285 4620278199966380988 4613774491979221856] I know the proper way of changing is: c = c.astype(int) But I want to the reason behind those ambiguous numbers

Display multiple output tables in IPython notebook using Pandas

由 落爺英雄遲暮 提交于 2020-01-11 05:11:05
问题 I now know that I can output multiple charts from IPython pandas by embedding them in one plot space which will appear in a single output cell in the notebook. Can I do something similar with Pandas HTML Tables? I am getting data from multiple tabs (about 15-20) on a spreadsheet and running them though a set of regressions and I'd like to display the results together, perhaps 2 up.. But since the function to display the table only displays one, the last one, not sure how to approach. Ideas? I

Interactive matplotlib using ipywidgets

由 戏子无情 提交于 2020-01-11 04:39:08
问题 I want to implement an interactive plot using Matplotlib and ipywidgets in IPython (python3). So, how I can do this efficiently (change smoothly without delay)? And another question is why this code works?! from ipywidgets import * import numpy as np import matplotlib.pyplot as plt %matplotlib inline x = np.linspace(0, 2 * np.pi) def update(w = 1.0): fig = plt.figure() ax = fig.add_subplot(1, 1, 1) ax.plot(x, np.sin(w * x)) fig.canvas.draw() interact(update); But, this doesn't work?! from

运用Jupyter Notebook进行系统管理

由 谁说我不能喝 提交于 2020-01-10 09:26:49
【推荐】2019 Java 开发者跳槽指南.pdf(吐血整理) >>> Jupyter Notebook可以将系统信息作为页面进行展示，将python等信息和shell等执行工具集成到统一的页面（参考《 IPython 6/Jupyter的magic操作符 》、 IPython的Magics魔法操作符 ），从而提供一个完整的自定义动态视图。Jupyter Notebook Server还提供Text/HTML/Markdown/JSON/YAML等多种文档编辑器以及可以打开多个并随意布局的Web shell支持，不仅可用于数据分析，也是系统管理、维护的利器。 上图，在Notebook中运行GlusterFS存储系统和Kubernetes的管理工具。 1、安装步骤 包括： JupyterLab的本地安装和使用（Ubuntu 18.04） 将Jupyter/JupyterHub/JupyterLab运行为系统服务 Jupyter notebook中的sudo问题详解 2、使用方法 Jupyter Notebook是在服务器上运行的，默认是安装（或服务）的账号。因此，所有的状态是持续的，上次打开的窗口下次在任何地方打开都是上次的状态，如果多个页面同时打开，普通页面可以刷新同步，终端shell是自动更新的。 Python代码 普通的python代码在打开notebook后，输入代码

ValueError: index must be monotonic increasing or decreasing

由 余生颓废 提交于 2020-01-10 05:38:06
问题 ser3 = Series(['USA','Mexico','Canada'],index = ['0','5','10']) here ranger = range(15) I get an error while using Forward fill in iPython ser3.reindex(ranger,method = 'ffill') /Users/varun/anaconda/lib/python2.7/site-packages/pandas/core/index.pyc in _searchsorted_monotonic(self, label, side) 2395 return len(self) - pos 2396 -> 2397 raise ValueError('index must be monotonic increasing or decreasing') 2398 2399 def get_slice_bound(self, label, side, kind): ValueError: index must be monotonic

IPython sys.path different from python sys.path

由 独自空忆成欢 提交于 2020-01-10 03:56:08
问题 I generally use IPython and only recently noticed that the the search path for imports is wrong in the regular python shell. From what I understand, sys.path inherits from PYTHONPATH (although I don't know where PYTHONPATH lives), is this different in IPython? I'm worried that this effecting installations. For instance I just tried pip install --upgrade gensim which failed because it couldn't resolve the scipy dependency, which I already have installed. So I dove a little bit deeper and found

ipython --pylab vs ipython

由 一世执手 提交于 2020-01-09 14:31:27
问题 What does ipython --pylab exactly do? Is ipython --pylab exactly equivalent to: > ipython > from pylab import * If not, what are the differences? Say I launch IPython without the --pylab arguments, how can I bring it to the same state as if I had started it with --pylab ? 回答1: --pylab[=option] is almost technically equivalent to %pylab option as the difference that you cannot un-pylab a --pylab kernel, but you can restart a %pylab kernel. %pylab is a little more that just from pylab import *

ipython --pylab vs ipython

由 一笑奈何 提交于 2020-01-09 14:30:27
问题 What does ipython --pylab exactly do? Is ipython --pylab exactly equivalent to: > ipython > from pylab import * If not, what are the differences? Say I launch IPython without the --pylab arguments, how can I bring it to the same state as if I had started it with --pylab ? 回答1: --pylab[=option] is almost technically equivalent to %pylab option as the difference that you cannot un-pylab a --pylab kernel, but you can restart a %pylab kernel. %pylab is a little more that just from pylab import *
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