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Commit 35534c45 authored by Vikrant Rajan's avatar Vikrant Rajan
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Bokeh Motion Detection

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Face Detection/Motion Detection App/Graph.html 0 → 100644
View file @ 35534c45
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>Bokeh Plot</title>
<script type="text/javascript" src="https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js"></script>
<script type="text/javascript">
Bokeh.set_log_level("info");
</script>
</head>
<body>
<div class="bk-root" id="b03d2ed8-a7a1-499f-aa5f-c22c979ff227" data-root-id="1001"></div>
<script type="application/json" id="1282">
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</script>
<script type="text/javascript">
(function() {
var fn = function() {
Bokeh.safely(function() {
(function(root) {
function embed_document(root) {
var docs_json = document.getElementById('1282').textContent;
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console.log("Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing");
}
}
}, 10, root)
}
})(window);
});
};
if (document.readyState != "loading") fn();
else document.addEventListener("DOMContentLoaded", fn);
})();
</script>
</body>
</html>
\ No newline at end of file
Face Detection/Motion Detection App/Graph1.html 0 → 100644
View file @ 35534c45
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>Bokeh Plot</title>
<script type="text/javascript" src="https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js"></script>
<script type="text/javascript">
Bokeh.set_log_level("info");
</script>
</head>
<body>
<div class="bk-root" id="c856ed81-fc51-4993-a543-b1953e0f27f1" data-root-id="1002"></div>
<script type="application/json" id="1283">
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<script type="text/javascript">
(function() {
var fn = function() {
Bokeh.safely(function() {
(function(root) {
function embed_document(root) {
var docs_json = document.getElementById('1283').textContent;
var render_items = [{"docid":"1e600da5-6854-4e5d-8c7a-fbc2592df22a","roots":{"1002":"c856ed81-fc51-4993-a543-b1953e0f27f1"}}];
root.Bokeh.embed.embed_items(docs_json, render_items);
}
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embed_document(root);
} else {
var attempts = 0;
var timer = setInterval(function(root) {
if (root.Bokeh !== undefined) {
clearInterval(timer);
embed_document(root);
} else {
attempts++;
if (attempts > 100) {
clearInterval(timer);
console.log("Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing");
}
}
}, 10, root)
}
})(window);
});
};
if (document.readyState != "loading") fn();
else document.addEventListener("DOMContentLoaded", fn);
})();
</script>
</body>
</html>
\ No newline at end of file
Face Detection/Motion Detection App/Times.csv 0 → 100644
View file @ 35534c45
,Start,End
0,2019-12-27 12:34:18.106721,2019-12-27 12:34:21.697614
Face Detection/Motion Detection App/capture.py 0 → 100644
View file @ 35534c45
"""
MOTION DETECTION APPLICATION
"""
import cv2, time, pandas
from datetime import datetime
first_frame = None
status_list = [None, None]
times = []
df = pandas.DataFrame(columns=["Start", "End"])
video = cv2.VideoCapture(0)
while True:
check, frame = video.read()
# 0 = nothing is moving, 1 = motion detected
status = 0
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (21, 21), 0)
if first_frame is None:
first_frame = gray
continue
delta_frame = cv2.absdiff(first_frame, gray)
thresh_frame = cv2.threshold(delta_frame, 30, 255, cv2.THRESH_BINARY)[1]
thresh_frame = cv2.dilate(thresh_frame, None, iterations=2)
(cnts,__) = cv2.findContours(thresh_frame.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
for contour in cnts:
# checking the area of the objects in camera
if cv2.contourArea(contour) < 10000:
continue
status = 1
(x, y, w, h) = cv2.boundingRect(contour)
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 3)
status_list.append(status)
status_list = status_list[-2:]
if status_list[-1] == 1 and status_list[-2] == 0:
times.append(datetime.now())
if status_list[-1] == 0 and status_list[-2] == 1:
times.append(datetime.now())
cv2.imshow("Gray Frame", gray)
cv2.imshow("Delta Frame",delta_frame)
cv2.imshow("Threshold Frame",thresh_frame)
cv2.imshow("Color Frame", frame)
key = cv2.waitKey(1)
if key == ord('q'):
if status == 1:
times.append(datetime.now())
break
print(status_list)
print(times)
for i in range(0, len(times), 2):
df = df.append({"Start":times[i], "End": times[i+1]}, ignore_index=True)
df.to_csv("Times.csv")
video.release()
cv2.destroyAllWindows
\ No newline at end of file
Face Detection/Motion Detection App/plotting.py 0 → 100644
View file @ 35534c45
from capture import df
from bokeh.plotting import figure, show, output_file
from bokeh.models import HoverTool, ColumnDataSource
df["Start_string"] = df["Start"].dt.strftime("%Y-%m-%d %H:%M:%S")
df["End_string"] = df["End"].dt.strftime("%Y-%m-%d %H:%M:%S")
cds = ColumnDataSource(df)
p = figure(x_axis_type = "datetime", height = 300, width = 1000, title = "Motion Graph")
p.yaxis.minor_tick_line_color = None
p.ygrid[0].ticker.desired_num_ticks = 1
hover = HoverTool(tooltips = [("Start", "@Start_string"),("End", "@End_string")])
p.add_tools(hover)
q = p.quad(left="Start", right = "End", bottom = 0, top = 1, color = "green", source = cds)
output_file("Graph1.html")
show(p)
\ No newline at end of file
bokeh/.ipynb_checkpoints/Basic Graph-checkpoint.ipynb 0 → 100644
View file @ 35534c45
{
"cells": [],
"metadata": {},
"nbformat": 4,
"nbformat_minor": 2
}
bokeh/Basic Graph.ipynb 0 → 100644
View file @ 35534c45
{
"cells": [
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"# Making a basic Bokeh Line Graph\n",
"\n",
"from bokeh.plotting import figure\n",
"from bokeh.io import output_file, show\n",
"\n",
"# getting some data\n",
"x = [3, 4, 5]\n",
"y = [6, 2, 7]\n",
"\n",
"# creating an output file\n",
"output_file(\"datavisualization.html\")\n",
"\n",
"# creating a figure object\n",
"f = figure()\n",
"\n",
"# creating a line plot with ^ data above ^\n",
"f.line(x, y)\n",
"\n",
"show(f)\n"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"# Making a basic Bokeh Line Graph\n",
"\n",
"from bokeh.plotting import figure\n",
"from bokeh.io import output_file, show\n",
"import pandas\n",
"\n",
"# getting some data\n",
"df = pandas.read_csv(\"data.csv\")\n",
"x = df[\"x\"]\n",
"y = df[\"y\"]\n",
"\n",
"# creating an output file\n",
"output_file(\"csv_file.html\")\n",
"\n",
"# creating a figure object\n",
"f = figure()\n",
"\n",
"# creating a line plot with ^ data above ^\n",
"f.line(x, y)\n",
"\n",
"show(f)\n"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"# Making a basic Bokeh Line Graph\n",
"\n",
"from bokeh.plotting import figure\n",
"from bokeh.io import output_file, show\n",
"import pandas\n",
"\n",
"# getting some data\n",
"df = pandas.read_csv(\"http://pythonhow.com/data/bachelors.csv\")\n",
"x = df[\"Year\"]\n",
"y = df[\"Engineering\"]\n",
"\n",
"# creating an output file\n",
"output_file(\"csv_file_2.html\")\n",
"\n",
"# creating a figure object\n",
"f = figure()\n",
"\n",
"# creating a line plot with ^ data above ^\n",
"f.line(x, y)\n",
"\n",
"show(f)\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"scrolled": true
},
"outputs": [
{
"ename": "AttributeError",
"evalue": "unexpected attribute 'logo' to Figure, possible attributes are above, align, aspect_ratio, aspect_scale, background, background_fill_alpha, background_fill_color, below, border_fill_alpha, border_fill_color, center, css_classes, disabled, extra_x_ranges, extra_y_ranges, frame_height, frame_width, height, height_policy, hidpi, inner_height, inner_width, js_event_callbacks, js_property_callbacks, left, lod_factor, lod_interval, lod_threshold, lod_timeout, margin, match_aspect, max_height, max_width, min_border, min_border_bottom, min_border_left, min_border_right, min_border_top, min_height, min_width, name, outer_height, outer_width, outline_line_alpha, outline_line_cap, outline_line_color, outline_line_dash, outline_line_dash_offset, outline_line_join, outline_line_width, output_backend, plot_height, plot_width, renderers, reset_policy, right, sizing_mode, subscribed_events, tags, title, title_location, toolbar, toolbar_location, toolbar_sticky, visible, width, width_policy, x_range, x_scale, y_range or y_scale",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-4-83d2c11ef81c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"Engineering\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m \u001b[0mp\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mplot_width\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m500\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mplot_height\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m400\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtools\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'pan'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlogo\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 11\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[0mp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtitle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtext\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"Cool Data\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/bokeh/plotting/figure.py\u001b[0m in \u001b[0;36mfigure\u001b[0;34m(**kwargs)\u001b[0m\n\u001b[1;32m 1240\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1241\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mfigure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1242\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mFigure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1243\u001b[0m \u001b[0mfigure\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mFigure\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1244\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/bokeh/plotting/figure.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, *arg, **kw)\u001b[0m\n\u001b[1;32m 151\u001b[0m \u001b[0mkw\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'title'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTitle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtext\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtitle\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 152\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 153\u001b[0;31m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mFigure\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__init__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0marg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 154\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 155\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mx_range\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_get_range\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mopts\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mx_range\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/bokeh/model.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m 316\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"id\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 317\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 318\u001b[0;31m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mModel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__init__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 319\u001b[0m \u001b[0mdefault_theme\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply_to_model\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 320\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/bokeh/core/has_props.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, **properties)\u001b[0m\n\u001b[1;32m 251\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 252\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mproperties\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 253\u001b[0;31m \u001b[0msetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 254\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 255\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/bokeh/core/has_props.py\u001b[0m in \u001b[0;36m__setattr__\u001b[0;34m(self, name, value)\u001b[0m\n\u001b[1;32m 285\u001b[0m \u001b[0mmatches\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtext\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mprops\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"possible\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 286\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 287\u001b[0;31m raise AttributeError(\"unexpected attribute '%s' to %s, %s attributes are %s\" %\n\u001b[0m\u001b[1;32m 288\u001b[0m (name, self.__class__.__name__, text, nice_join(matches)))\n\u001b[1;32m 289\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mAttributeError\u001b[0m: unexpected attribute 'logo' to Figure, possible attributes are above, align, aspect_ratio, aspect_scale, background, background_fill_alpha, background_fill_color, below, border_fill_alpha, border_fill_color, center, css_classes, disabled, extra_x_ranges, extra_y_ranges, frame_height, frame_width, height, height_policy, hidpi, inner_height, inner_width, js_event_callbacks, js_property_callbacks, left, lod_factor, lod_interval, lod_threshold, lod_timeout, margin, match_aspect, max_height, max_width, min_border, min_border_bottom, min_border_left, min_border_right, min_border_top, min_height, min_width, name, outer_height, outer_width, outline_line_alpha, outline_line_cap, outline_line_color, outline_line_dash, outline_line_dash_offset, outline_line_join, outline_line_width, output_backend, plot_height, plot_width, renderers, reset_policy, right, sizing_mode, subscribed_events, tags, title, title_location, toolbar, toolbar_location, toolbar_sticky, visible, width, width_policy, x_range, x_scale, y_range or y_scale"
]
}
],
"source": [
"from bokeh.plotting import figure\n",
"from bokeh.io import output_file, show\n",
"import pandas\n",
"\n",
"# getting some data\n",
"df = pandas.read_csv(\"http://pythonhow.com/data/bachelors.csv\")\n",
"x = df[\"Year\"]\n",
"y = df[\"Engineering\"]\n",
" \n",
"p=figure(plot_width=500,plot_height=400, tools='pan',logo=None)\n",
" \n",
"p.title.text=\"Cool Data\"\n",
"p.title.text_color=\"Gray\"\n",
"p.title.text_font=\"times\"\n",
"p.title.text_font_style=\"bold\"\n",
"p.xaxis.minor_tick_line_color=None\n",
"p.yaxis.minor_tick_line_color=None\n",
"p.xaxis.axis_label=\"Date\"\n",
"p.yaxis.axis_label=\"Intensity\" \n",
" \n",
"p.line(x,y)\n",
"output_file(\"graph.html\")\n",
"show(p)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"import pandas\n",
" \n",
"from bokeh.plotting import figure, output_file, show\n",
" \n",
"df=pandas.read_excel(\"http://pythonhow.com/data/verlegenhuken.xlsx\",sheet_name=0)\n",
"df[\"Temperature\"]=df[\"Temperature\"]/10\n",
"df[\"Pressure\"]=df[\"Pressure\"]/10\n",
" \n",
"p=figure(plot_width=500,plot_height=400,tools='pan')\n",
" \n",
"p.title.text=\"Temperature and Air Pressure\"\n",
"p.title.text_color=\"Gray\"\n",
"p.title.text_font=\"arial\"\n",
"p.title.text_font_style=\"bold\"\n",
"p.xaxis.minor_tick_line_color=None\n",
"p.yaxis.minor_tick_line_color=None\n",
"p.xaxis.axis_label=\"Temperature (°C)\"\n",
"p.yaxis.axis_label=\"Pressure (hPa)\" \n",
" \n",
"p.circle(df[\"Temperature\"],df[\"Pressure\"],size=0.5)\n",
"output_file(\"Weather.html\")\n",
"show(p)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"import pandas\n",
"from bokeh.plotting import figure, output_file, show\n",
"\n",
"df=pandas.read_csv(\"adbe.csv\",parse_dates=[\"Date\"])\n",
"\n",
"p=figure(width=500, height=250, x_axis_type=\"datetime\")\n",
"\n",
"p.line(df[\"Date\"], df[\"Close\"], color=\"Orange\", alpha = 0.5)\n",
"\n",
"output_file(\"Timeseries.html\")\n",
"show(p)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.0"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
%% Cell type:code id: tags:
``` python
# Making a basic Bokeh Line Graph
from bokeh.plotting import figure
from bokeh.io import output_file, show
# getting some data
x = [3, 4, 5]
y = [6, 2, 7]
# creating an output file
output_file("datavisualization.html")
# creating a figure object
f = figure()
# creating a line plot with ^ data above ^
f.line(x, y)
show(f)
```
%% Cell type:code id: tags:
``` python
# Making a basic Bokeh Line Graph
from bokeh.plotting import figure
from bokeh.io import output_file, show
import pandas
# getting some data
df = pandas.read_csv("data.csv")
x = df["x"]
y = df["y"]