Skip to content

Commit f0c5b48

Browse files
author
Guilherme Samora
committed
update data link titanic
1 parent 7fa9485 commit f0c5b48

File tree

3 files changed

+30
-72
lines changed

3 files changed

+30
-72
lines changed

‎07_Visualization/Titanic_Desaster/Exercises.ipynb

+10-24
Original file line numberDiff line numberDiff line change
@@ -23,17 +23,15 @@
2323
{
2424
"cell_type": "code",
2525
"execution_count": null,
26-
"metadata": {
27-
"collapsed": false
28-
},
26+
"metadata": {},
2927
"outputs": [],
3028
"source": []
3129
},
3230
{
3331
"cell_type": "markdown",
3432
"metadata": {},
3533
"source": [
36-
"### Step 2. Import the dataset from this [address](https://raw.githubusercontent.com/guipsamora/pandas_exercises/master/Visualization/Titanic_Desaster/train.csv). "
34+
"### Step 2. Import the dataset from this [address](https://raw.githubusercontent.com/guipsamora/pandas_exercises/master/07_Visualization/Titanic_Desaster/train.csv)"
3735
]
3836
},
3937
{
@@ -46,9 +44,7 @@
4644
{
4745
"cell_type": "code",
4846
"execution_count": null,
49-
"metadata": {
50-
"collapsed": false
51-
},
47+
"metadata": {},
5248
"outputs": [],
5349
"source": []
5450
},
@@ -62,9 +58,7 @@
6258
{
6359
"cell_type": "code",
6460
"execution_count": null,
65-
"metadata": {
66-
"collapsed": false
67-
},
61+
"metadata": {},
6862
"outputs": [],
6963
"source": []
7064
},
@@ -78,9 +72,7 @@
7872
{
7973
"cell_type": "code",
8074
"execution_count": null,
81-
"metadata": {
82-
"collapsed": false
83-
},
75+
"metadata": {},
8476
"outputs": [],
8577
"source": []
8678
},
@@ -94,9 +86,7 @@
9486
{
9587
"cell_type": "code",
9688
"execution_count": null,
97-
"metadata": {
98-
"collapsed": false
99-
},
89+
"metadata": {},
10090
"outputs": [],
10191
"source": []
10292
},
@@ -110,9 +100,7 @@
110100
{
111101
"cell_type": "code",
112102
"execution_count": null,
113-
"metadata": {
114-
"collapsed": false
115-
},
103+
"metadata": {},
116104
"outputs": [],
117105
"source": []
118106
},
@@ -126,9 +114,7 @@
126114
{
127115
"cell_type": "code",
128116
"execution_count": null,
129-
"metadata": {
130-
"collapsed": false
131-
},
117+
"metadata": {},
132118
"outputs": [],
133119
"source": []
134120
},
@@ -165,9 +151,9 @@
165151
"name": "python",
166152
"nbconvert_exporter": "python",
167153
"pygments_lexer": "ipython2",
168-
"version": "2.7.11"
154+
"version": "2.7.16"
169155
}
170156
},
171157
"nbformat": 4,
172-
"nbformat_minor": 0
158+
"nbformat_minor": 1
173159
}

‎07_Visualization/Titanic_Desaster/Exercises_code_with_solutions.ipynb

+10-24
Original file line numberDiff line numberDiff line change
@@ -23,9 +23,7 @@
2323
{
2424
"cell_type": "code",
2525
"execution_count": 2,
26-
"metadata": {
27-
"collapsed": false
28-
},
26+
"metadata": {},
2927
"outputs": [],
3028
"source": [
3129
"import pandas as pd\n",
@@ -40,7 +38,7 @@
4038
"cell_type": "markdown",
4139
"metadata": {},
4240
"source": [
43-
"### Step 2. Import the dataset from this [address](https://raw.githubusercontent.com/guipsamora/pandas_exercises/master/Visualization/Titanic_Desaster/train.csv). "
41+
"### Step 2. Import the dataset from this [address](https://raw.githubusercontent.com/guipsamora/pandas_exercises/master/07_Visualization/Titanic_Desaster/train.csv) "
4442
]
4543
},
4644
{
@@ -53,9 +51,7 @@
5351
{
5452
"cell_type": "code",
5553
"execution_count": 4,
56-
"metadata": {
57-
"collapsed": false
58-
},
54+
"metadata": {},
5955
"outputs": [
6056
{
6157
"data": {
@@ -205,9 +201,7 @@
205201
{
206202
"cell_type": "code",
207203
"execution_count": 5,
208-
"metadata": {
209-
"collapsed": false
210-
},
204+
"metadata": {},
211205
"outputs": [
212206
{
213207
"data": {
@@ -364,9 +358,7 @@
364358
{
365359
"cell_type": "code",
366360
"execution_count": 24,
367-
"metadata": {
368-
"collapsed": false
369-
},
361+
"metadata": {},
370362
"outputs": [
371363
{
372364
"data": {
@@ -432,9 +424,7 @@
432424
{
433425
"cell_type": "code",
434426
"execution_count": 67,
435-
"metadata": {
436-
"collapsed": false
437-
},
427+
"metadata": {},
438428
"outputs": [
439429
{
440430
"data": {
@@ -480,9 +470,7 @@
480470
{
481471
"cell_type": "code",
482472
"execution_count": 68,
483-
"metadata": {
484-
"collapsed": false
485-
},
473+
"metadata": {},
486474
"outputs": [
487475
{
488476
"data": {
@@ -509,9 +497,7 @@
509497
{
510498
"cell_type": "code",
511499
"execution_count": 48,
512-
"metadata": {
513-
"collapsed": false
514-
},
500+
"metadata": {},
515501
"outputs": [
516502
{
517503
"data": {
@@ -578,9 +564,9 @@
578564
"name": "python",
579565
"nbconvert_exporter": "python",
580566
"pygments_lexer": "ipython2",
581-
"version": "2.7.11"
567+
"version": "2.7.16"
582568
}
583569
},
584570
"nbformat": 4,
585-
"nbformat_minor": 0
571+
"nbformat_minor": 1
586572
}

‎07_Visualization/Titanic_Desaster/Solutions.ipynb

+10-24
Original file line numberDiff line numberDiff line change
@@ -23,9 +23,7 @@
2323
{
2424
"cell_type": "code",
2525
"execution_count": 80,
26-
"metadata": {
27-
"collapsed": false
28-
},
26+
"metadata": {},
2927
"outputs": [],
3028
"source": [
3129
"import pandas as pd\n",
@@ -40,7 +38,7 @@
4038
"cell_type": "markdown",
4139
"metadata": {},
4240
"source": [
43-
"### Step 2. Import the dataset from this [address](https://raw.githubusercontent.com/guipsamora/pandas_exercises/master/Visualization/Titanic_Desaster/train.csv). "
41+
"### Step 2. Import the dataset from this [address](https://raw.githubusercontent.com/guipsamora/pandas_exercises/master/07_Visualization/Titanic_Desaster/train.csv) "
4442
]
4543
},
4644
{
@@ -53,9 +51,7 @@
5351
{
5452
"cell_type": "code",
5553
"execution_count": 23,
56-
"metadata": {
57-
"collapsed": false
58-
},
54+
"metadata": {},
5955
"outputs": [
6056
{
6157
"data": {
@@ -199,9 +195,7 @@
199195
{
200196
"cell_type": "code",
201197
"execution_count": 22,
202-
"metadata": {
203-
"collapsed": false
204-
},
198+
"metadata": {},
205199
"outputs": [
206200
{
207201
"data": {
@@ -356,9 +350,7 @@
356350
{
357351
"cell_type": "code",
358352
"execution_count": 24,
359-
"metadata": {
360-
"collapsed": false
361-
},
353+
"metadata": {},
362354
"outputs": [
363355
{
364356
"data": {
@@ -383,9 +375,7 @@
383375
{
384376
"cell_type": "code",
385377
"execution_count": 67,
386-
"metadata": {
387-
"collapsed": false
388-
},
378+
"metadata": {},
389379
"outputs": [
390380
{
391381
"data": {
@@ -420,9 +410,7 @@
420410
{
421411
"cell_type": "code",
422412
"execution_count": 68,
423-
"metadata": {
424-
"collapsed": false
425-
},
413+
"metadata": {},
426414
"outputs": [
427415
{
428416
"data": {
@@ -447,9 +435,7 @@
447435
{
448436
"cell_type": "code",
449437
"execution_count": 93,
450-
"metadata": {
451-
"collapsed": false
452-
},
438+
"metadata": {},
453439
"outputs": [
454440
{
455441
"data": {
@@ -497,9 +483,9 @@
497483
"name": "python",
498484
"nbconvert_exporter": "python",
499485
"pygments_lexer": "ipython2",
500-
"version": "2.7.11"
486+
"version": "2.7.16"
501487
}
502488
},
503489
"nbformat": 4,
504-
"nbformat_minor": 0
490+
"nbformat_minor": 1
505491
}

0 commit comments

Comments
 (0)