typo fix

rasbt · rasbt · commit 447f588960ec · 2014-07-31T00:20:22.000-04:00
diff --git a/tutorials/example.csv b/tutorials/example.csv
@@ -0,0 +1,3 @@
+1,2,3,4
+5,6,,8
+10,11,12,
diff --git a/tutorials/numpy_nan_quickguide.ipynb b/tutorials/numpy_nan_quickguide.ipynb
@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:7553ded8e8dc9e6faf09cd22747b33a3ae9039743491e88025fb61ea45203063"
+  "signature": "sha256:b2597ea4263c11dd6774b227e7a3a5626197c4863e6895002657fd55d02b55d9"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -39,10 +39,10 @@
        "output_type": "stream",
        "stream": "stdout",
        "text": [
-        "Last updated: 30/07/2014 \n",
+        "Last updated: 31/07/2014 \n",
         "\n",
         "CPython 3.4.1\n",
-        "IPython 2.0.0\n",
+        "IPython 2.1.0\n",
         "\n",
         "numpy 1.8.1\n"
        ]
@@ -161,7 +161,7 @@
        "output_type": "stream",
        "stream": "stdout",
        "text": [
-        "Overwriting example.csv\n"
+        "Writing example.csv\n"
        ]
       }
      ],
@@ -258,13 +258,13 @@
       {
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 37,
+       "prompt_number": 5,
        "text": [
         "True"
        ]
       }
      ],
-     "prompt_number": 37
+     "prompt_number": 5
     },
     {
      "cell_type": "markdown",
@@ -292,15 +292,15 @@
       {
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 5,
+       "prompt_number": 6,
        "text": [
         "array([[False, False, False, False],\n",
         "       [False, False,  True, False],\n",
         "       [False, False, False,  True]], dtype=bool)"
        ]
       }
      ],
-     "prompt_number": 5
+     "prompt_number": 6
     },
     {
      "cell_type": "markdown",
@@ -351,13 +351,13 @@
       {
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 8,
+       "prompt_number": 7,
        "text": [
         "2"
        ]
       }
      ],
-     "prompt_number": 8
+     "prompt_number": 7
     },
     {
      "cell_type": "markdown",
@@ -385,13 +385,13 @@
       {
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 9,
+       "prompt_number": 8,
        "text": [
         "10"
        ]
       }
      ],
-     "prompt_number": 9
+     "prompt_number": 8
     },
     {
      "cell_type": "markdown",
@@ -435,13 +435,13 @@
       {
        "metadata": {},
        "output_type": "pyout",
-       "prompt_number": 10,
+       "prompt_number": 9,
        "text": [
         "nan"
        ]
       }
      ],
-     "prompt_number": 10
+     "prompt_number": 9
     },
     {
      "cell_type": "markdown",
@@ -474,13 +474,13 @@
        ]
       }
      ],
-     "prompt_number": 11
+     "prompt_number": 10
     },
     {
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "print('row sums:', np.nansum(ary, axis=0))"
+      "print('column sums:', np.nansum(ary, axis=0))"
      ],
      "language": "python",
      "metadata": {},
@@ -489,17 +489,17 @@
        "output_type": "stream",
        "stream": "stdout",
        "text": [
-        "row sums: [ 16.  19.  15.  12.]\n"
+        "column sums: [ 16.  19.  15.  12.]\n"
        ]
       }
      ],
-     "prompt_number": 12
+     "prompt_number": 11
     },
     {
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "print('column sums:', np.nansum(ary, axis=1))"
+      "print('row sums:', np.nansum(ary, axis=1))"
      ],
      "language": "python",
      "metadata": {},
@@ -508,11 +508,11 @@
        "output_type": "stream",
        "stream": "stdout",
        "text": [
-        "column sums: [ 10.  19.  33.]\n"
+        "row sums: [ 10.  19.  33.]\n"
        ]
       }
      ],
-     "prompt_number": 13
+     "prompt_number": 12
     },
     {
      "cell_type": "markdown",

Original file line number	Diff line number	Diff line change
`@@ -1,7 +1,7 @@`
`1`	`1`	`{`
`2`	`2`	`"metadata": {`
`3`	`3`	`"name": "",`
`4`		`- "signature": "sha256:7553ded8e8dc9e6faf09cd22747b33a3ae9039743491e88025fb61ea45203063"`
	`4`	`+ "signature": "sha256:b2597ea4263c11dd6774b227e7a3a5626197c4863e6895002657fd55d02b55d9"`
`5`	`5`	`},`
`6`	`6`	`"nbformat": 3,`
`7`	`7`	`"nbformat_minor": 0,`
`@@ -39,10 +39,10 @@`
`39`	`39`	`"output_type": "stream",`
`40`	`40`	`"stream": "stdout",`
`41`	`41`	`"text": [`
`42`		`- "Last updated: 30/07/2014 \n",`
	`42`	`+ "Last updated: 31/07/2014 \n",`
`43`	`43`	`"\n",`
`44`	`44`	`"CPython 3.4.1\n",`
`45`		`- "IPython 2.0.0\n",`
	`45`	`+ "IPython 2.1.0\n",`
`46`	`46`	`"\n",`
`47`	`47`	`"numpy 1.8.1\n"`
`48`	`48`	`]`
`@@ -161,7 +161,7 @@`
`161`	`161`	`"output_type": "stream",`
`162`	`162`	`"stream": "stdout",`
`163`	`163`	`"text": [`
`164`		`- "Overwriting example.csv\n"`
	`164`	`+ "Writing example.csv\n"`
`165`	`165`	`]`
`166`	`166`	`}`
`167`	`167`	`],`
`@@ -258,13 +258,13 @@`
`258`	`258`	`{`
`259`	`259`	`"metadata": {},`
`260`	`260`	`"output_type": "pyout",`
`261`		`- "prompt_number": 37,`
	`261`	`+ "prompt_number": 5,`
`262`	`262`	`"text": [`
`263`	`263`	`"True"`
`264`	`264`	`]`
`265`	`265`	`}`
`266`	`266`	`],`
`267`		`- "prompt_number": 37`
	`267`	`+ "prompt_number": 5`
`268`	`268`	`},`
`269`	`269`	`{`
`270`	`270`	`"cell_type": "markdown",`
`@@ -292,15 +292,15 @@`
`292`	`292`	`{`
`293`	`293`	`"metadata": {},`
`294`	`294`	`"output_type": "pyout",`
`295`		`- "prompt_number": 5,`
	`295`	`+ "prompt_number": 6,`
`296`	`296`	`"text": [`
`297`	`297`	`"array([[False, False, False, False],\n",`
`298`	`298`	`" [False, False, True, False],\n",`
`299`	`299`	`" [False, False, False, True]], dtype=bool)"`
`300`	`300`	`]`
`301`	`301`	`}`
`302`	`302`	`],`
`303`		`- "prompt_number": 5`
	`303`	`+ "prompt_number": 6`
`304`	`304`	`},`
`305`	`305`	`{`
`306`	`306`	`"cell_type": "markdown",`
`@@ -351,13 +351,13 @@`
`351`	`351`	`{`
`352`	`352`	`"metadata": {},`
`353`	`353`	`"output_type": "pyout",`
`354`		`- "prompt_number": 8,`
	`354`	`+ "prompt_number": 7,`
`355`	`355`	`"text": [`
`356`	`356`	`"2"`
`357`	`357`	`]`
`358`	`358`	`}`
`359`	`359`	`],`
`360`		`- "prompt_number": 8`
	`360`	`+ "prompt_number": 7`
`361`	`361`	`},`
`362`	`362`	`{`
`363`	`363`	`"cell_type": "markdown",`
`@@ -385,13 +385,13 @@`
`385`	`385`	`{`
`386`	`386`	`"metadata": {},`
`387`	`387`	`"output_type": "pyout",`
`388`		`- "prompt_number": 9,`
	`388`	`+ "prompt_number": 8,`
`389`	`389`	`"text": [`
`390`	`390`	`"10"`
`391`	`391`	`]`
`392`	`392`	`}`
`393`	`393`	`],`
`394`		`- "prompt_number": 9`
	`394`	`+ "prompt_number": 8`
`395`	`395`	`},`
`396`	`396`	`{`
`397`	`397`	`"cell_type": "markdown",`
`@@ -435,13 +435,13 @@`
`435`	`435`	`{`
`436`	`436`	`"metadata": {},`
`437`	`437`	`"output_type": "pyout",`
`438`		`- "prompt_number": 10,`
	`438`	`+ "prompt_number": 9,`
`439`	`439`	`"text": [`
`440`	`440`	`"nan"`
`441`	`441`	`]`
`442`	`442`	`}`
`443`	`443`	`],`
`444`		`- "prompt_number": 10`
	`444`	`+ "prompt_number": 9`
`445`	`445`	`},`
`446`	`446`	`{`
`447`	`447`	`"cell_type": "markdown",`
`@@ -474,13 +474,13 @@`
`474`	`474`	`]`
`475`	`475`	`}`
`476`	`476`	`],`
`477`		`- "prompt_number": 11`
	`477`	`+ "prompt_number": 10`
`478`	`478`	`},`
`479`	`479`	`{`
`480`	`480`	`"cell_type": "code",`
`481`	`481`	`"collapsed": false,`
`482`	`482`	`"input": [`
`483`		`- "print('row sums:', np.nansum(ary, axis=0))"`
	`483`	`+ "print('column sums:', np.nansum(ary, axis=0))"`
`484`	`484`	`],`
`485`	`485`	`"language": "python",`
`486`	`486`	`"metadata": {},`
`@@ -489,17 +489,17 @@`
`489`	`489`	`"output_type": "stream",`
`490`	`490`	`"stream": "stdout",`
`491`	`491`	`"text": [`
`492`		`- "row sums: [ 16. 19. 15. 12.]\n"`
	`492`	`+ "column sums: [ 16. 19. 15. 12.]\n"`
`493`	`493`	`]`
`494`	`494`	`}`
`495`	`495`	`],`
`496`		`- "prompt_number": 12`
	`496`	`+ "prompt_number": 11`
`497`	`497`	`},`
`498`	`498`	`{`
`499`	`499`	`"cell_type": "code",`
`500`	`500`	`"collapsed": false,`
`501`	`501`	`"input": [`
`502`		`- "print('column sums:', np.nansum(ary, axis=1))"`
	`502`	`+ "print('row sums:', np.nansum(ary, axis=1))"`
`503`	`503`	`],`
`504`	`504`	`"language": "python",`
`505`	`505`	`"metadata": {},`
`@@ -508,11 +508,11 @@`
`508`	`508`	`"output_type": "stream",`
`509`	`509`	`"stream": "stdout",`
`510`	`510`	`"text": [`
`511`		`- "column sums: [ 10. 19. 33.]\n"`
	`511`	`+ "row sums: [ 10. 19. 33.]\n"`
`512`	`512`	`]`
`513`	`513`	`}`
`514`	`514`	`],`
`515`		`- "prompt_number": 13`
	`515`	`+ "prompt_number": 12`
`516`	`516`	`},`
`517`	`517`	`{`
`518`	`518`	`"cell_type": "markdown",`