Skip to content

Commit 6f932d7

Browse files
andrewhnberryandrewhnberry
committed
Update seaborn_exercise
-Improved Readability
1 parent 25905ae commit 6f932d7

File tree

3 files changed

+465
-6
lines changed

3 files changed

+465
-6
lines changed

‎.ipynb_checkpoints/plotly_exercise-checkpoint.ipynb

+240
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,240 @@
1+
{
2+
"cells": [
3+
{
4+
"cell_type": "code",
5+
"execution_count": null,
6+
"metadata": {
7+
"ExecuteTime": {
8+
"end_time": "2020-04-23T18:26:07.447844Z",
9+
"start_time": "2020-04-23T18:26:07.441869Z"
10+
}
11+
},
12+
"outputs": [],
13+
"source": [
14+
"# import plotly graph objects\n",
15+
"import plotly.graph_objs as go\n",
16+
"\n",
17+
"# import pandas\n",
18+
"import pandas as pd"
19+
]
20+
},
21+
{
22+
"cell_type": "markdown",
23+
"metadata": {},
24+
"source": [
25+
"# Objective: Create a scatterplot of 1000 random data points. \n",
26+
"x-axis values should come from a normal distribution using np.random.randn(1000). \n",
27+
"y-axis values should come from a uniform distribution over [0,1) using np.random.rand(1000)"
28+
]
29+
},
30+
{
31+
"cell_type": "code",
32+
"execution_count": null,
33+
"metadata": {
34+
"ExecuteTime": {
35+
"end_time": "2020-04-23T18:26:07.909854Z",
36+
"start_time": "2020-04-23T18:26:07.906289Z"
37+
}
38+
},
39+
"outputs": [],
40+
"source": [
41+
"# obtain x and y values:\n",
42+
"\n",
43+
"\n",
44+
"\n",
45+
"# define a data variable\n",
46+
"\n",
47+
"\n",
48+
"# define the layout, and include a title and axis labels\n",
49+
"\n",
50+
"\n",
51+
"# Create a fig from data and layout, and plot the fig\n"
52+
]
53+
},
54+
{
55+
"cell_type": "markdown",
56+
"metadata": {},
57+
"source": [
58+
"# Objective: Create a stacked bar chart. Note that questions appear in the index (and should be used for the x-axis), while responses appear as column labels. \n",
59+
"Extra Credit: make a horizontal bar chart! See https://plot.ly/python/horizontal-bar-charts/ for extra credit help."
60+
]
61+
},
62+
{
63+
"cell_type": "code",
64+
"execution_count": null,
65+
"metadata": {
66+
"ExecuteTime": {
67+
"end_time": "2020-04-23T18:26:08.379200Z",
68+
"start_time": "2020-04-23T18:26:08.282163Z"
69+
}
70+
},
71+
"outputs": [],
72+
"source": [
73+
"# load data\n",
74+
"df = pd.read_csv('https://raw.githubusercontent.com/Pierian-Data/Plotly-Dashboards-with-Dash/master/Data/mocksurvey.csv',index_col=0)"
75+
]
76+
},
77+
{
78+
"cell_type": "code",
79+
"execution_count": null,
80+
"metadata": {
81+
"ExecuteTime": {
82+
"end_time": "2020-04-23T18:26:08.487873Z",
83+
"start_time": "2020-04-23T18:26:08.483109Z"
84+
}
85+
},
86+
"outputs": [],
87+
"source": [
88+
"# create traces using a list comprehension:\n",
89+
"\n",
90+
"\n",
91+
"\n",
92+
"# create a layout, remember to set the barmode here\n",
93+
"\n",
94+
"\n",
95+
"\n",
96+
"\n",
97+
"# create a fig from data & layout, and plot the fig.\n",
98+
"\n",
99+
"\n"
100+
]
101+
},
102+
{
103+
"cell_type": "markdown",
104+
"metadata": {},
105+
"source": [
106+
"# Objective: Create a histogram that plots the 'length' field from dataset. Set the range from 0 to 1, with a bin size of 0.02"
107+
]
108+
},
109+
{
110+
"cell_type": "code",
111+
"execution_count": null,
112+
"metadata": {
113+
"ExecuteTime": {
114+
"end_time": "2020-04-23T18:26:09.057134Z",
115+
"start_time": "2020-04-23T18:26:08.854545Z"
116+
}
117+
},
118+
"outputs": [],
119+
"source": [
120+
"# load data\n",
121+
"df = pd.read_csv('https://raw.githubusercontent.com/Pierian-Data/Plotly-Dashboards-with-Dash/master/Data/abalone.csv')"
122+
]
123+
},
124+
{
125+
"cell_type": "code",
126+
"execution_count": null,
127+
"metadata": {
128+
"ExecuteTime": {
129+
"end_time": "2020-04-23T18:26:09.105535Z",
130+
"start_time": "2020-04-23T18:26:09.099657Z"
131+
}
132+
},
133+
"outputs": [],
134+
"source": [
135+
"# create a data variable:\n",
136+
"\n",
137+
"\n",
138+
"\n",
139+
"# add a layout\n",
140+
"\n",
141+
"\n",
142+
"\n",
143+
"\n",
144+
"# create a fig from data & layout, and plot the fig\n",
145+
"\n"
146+
]
147+
},
148+
{
149+
"cell_type": "code",
150+
"execution_count": null,
151+
"metadata": {},
152+
"outputs": [],
153+
"source": []
154+
},
155+
{
156+
"cell_type": "code",
157+
"execution_count": null,
158+
"metadata": {},
159+
"outputs": [],
160+
"source": []
161+
},
162+
{
163+
"cell_type": "code",
164+
"execution_count": null,
165+
"metadata": {},
166+
"outputs": [],
167+
"source": []
168+
},
169+
{
170+
"cell_type": "code",
171+
"execution_count": null,
172+
"metadata": {},
173+
"outputs": [],
174+
"source": []
175+
}
176+
],
177+
"metadata": {
178+
"kernelspec": {
179+
"display_name": "Python 3",
180+
"language": "python",
181+
"name": "python3"
182+
},
183+
"language_info": {
184+
"codemirror_mode": {
185+
"name": "ipython",
186+
"version": 3
187+
},
188+
"file_extension": ".py",
189+
"mimetype": "text/x-python",
190+
"name": "python",
191+
"nbconvert_exporter": "python",
192+
"pygments_lexer": "ipython3",
193+
"version": "3.7.4"
194+
},
195+
"toc": {
196+
"base_numbering": 1,
197+
"nav_menu": {},
198+
"number_sections": true,
199+
"sideBar": true,
200+
"skip_h1_title": false,
201+
"title_cell": "Table of Contents",
202+
"title_sidebar": "Contents",
203+
"toc_cell": false,
204+
"toc_position": {},
205+
"toc_section_display": true,
206+
"toc_window_display": false
207+
},
208+
"varInspector": {
209+
"cols": {
210+
"lenName": 16,
211+
"lenType": 16,
212+
"lenVar": 40
213+
},
214+
"kernels_config": {
215+
"python": {
216+
"delete_cmd_postfix": "",
217+
"delete_cmd_prefix": "del ",
218+
"library": "var_list.py",
219+
"varRefreshCmd": "print(var_dic_list())"
220+
},
221+
"r": {
222+
"delete_cmd_postfix": ") ",
223+
"delete_cmd_prefix": "rm(",
224+
"library": "var_list.r",
225+
"varRefreshCmd": "cat(var_dic_list()) "
226+
}
227+
},
228+
"types_to_exclude": [
229+
"module",
230+
"function",
231+
"builtin_function_or_method",
232+
"instance",
233+
"_Feature"
234+
],
235+
"window_display": false
236+
}
237+
},
238+
"nbformat": 4,
239+
"nbformat_minor": 2
240+
}

0 commit comments

Comments
 (0)