Created
February 6, 2015 06:50
-
-
Save yong27/1663c74272b7e685fdc2 to your computer and use it in GitHub Desktop.
plottest.ipynb
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
{ | |
"metadata": { | |
"name": "", | |
"signature": "sha256:9299994bc33725ce2fb54720efc2a7b1a7fb1e955d3914b9e8ba9de6a50bd456" | |
}, | |
"nbformat": 3, | |
"nbformat_minor": 0, | |
"worksheets": [ | |
{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"import pandas as pd\n", | |
"import numpy as np" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [], | |
"prompt_number": 10 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"ts = pd.Series(np.random.randn(1000))" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [], | |
"prompt_number": 13 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"ts = ts.cumsum()" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [], | |
"prompt_number": 15 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"ts.plot()" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 17, | |
"text": [ | |
"<matplotlib.axes._subplots.AxesSubplot at 0x10f5640f0>" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": "iVBORw0KGgoAAAANSUhEUgAAAYAAAAEACAYAAAC6d6FnAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngg==\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x10f545da0>" | |
] | |
} | |
], | |
"prompt_number": 17 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [] | |
} | |
], | |
"metadata": {} | |
} | |
] | |
} |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment