def make_mg_layout():
# load a dataframe
filename = "../examples/metricsgraphics/project/fitbit_data.csv"
df = pd.read_csv(filename)
# Make a UI
ui = UILayout("FilterChart")
# Make a Button
cols = [c for c in df.columns if c != "Date"]
btn = SelectButton("Data", cols, "Data", "Steps")
# add the button to the UI
ui.add_filter(btn)
# stack the dataframe
_stack = df.set_index("Date").stack().reset_index()
_stack = _stack.rename(columns={"level_1": "Data", 0: "value"})
# Make a Figure, add some settings, make a line plot
ui.add_chart(create_line_plot(_stack))
ui.add_chart(create_histogram(_stack))
ui.add_chart(create_scatterplot(df))
return ui
def make_mg_layout():
# load a dataframe
filename = "../examples/metricsgraphics/project/fitbit_data.csv"
df = pd.read_csv(filename)
# Make a UI
ui = UILayout("FilterChart")
# Make a Button
cols = [c for c in df.columns if c != "Date"]
btn = SelectButton("Data", cols, "Data", "Steps")
# add the button to the UI
ui.add_filter(btn)
# stack the dataframe
_stack = df.set_index("Date").stack().reset_index()
_stack = _stack.rename(columns={"level_1": "Data", 0: "value"})
# Make a Figure, add some settings, make a line plot
ui.add_chart(create_line_plot(_stack))
ui.add_chart(create_histogram(_stack))
ui.add_chart(create_scatterplot(df))
return ui
def make_table_layout():
filename = "../examples/datatables/project/static/data.json"
df = get_data(filename)
ui = UILayout("SimpleChart")
ui.add_chart(create_datatable(df))
return ui
def make_table_layout():
filename = "../examples/datatables/project/static/data.json"
df = get_data(filename)
ui = UILayout("SimpleChart")
ui.add_chart(create_datatable(df))
return ui
def make_datamaps_ui(filename):
# Make a UI
ui = UILayout("SimpleChart")
df = pd.read_csv(filename)
df.month = df.month.astype('str')
sldr = SliderInput("Month", 1, 13, "month", "1")
ui.add_filter(sldr)
dm = DatamapUSA("/data_map/", "mapid", df,
"state", "color1", init_params={"month": "1"})
ui.add_chart(dm)
return ui
def make_ui(datafiles):
# Make a UI
ui = UILayout(
"FilterChart",
"pyxley",
"component_id",
filter_style="''")
ff = fatigue(datafiles["scores"])
pf = load_players(datafiles["players"])
sf = distance_measures(datafiles["distance"], ff, pf)
df, _ids = split_teams(datafiles["locations"], pf, sf)
sf = pd.merge(sf, _ids, on=["game", "ngsId"], how='inner', sort=False)
_onfield = sf.loc[sf.isOnField == True].reset_index(drop=True)
_offfield = sf.loc[sf.isOnField == False].reset_index(drop=True)
sldr = SliderInput("new_index", 1, int(df["new_index"].max()), "new_index", "0")
# Read in the data and stack it, so that we can filter on columns
# Make a Button
games = ["game1", "game2", "game3"]
btnG = SelectButton("Game", games, "game", "game1")
# Make a FilterFrame and add the button to the UI
ui.add_filter(sldr)
ui.add_filter(btnG)
init_params = {
"game": "game1",
"new_index": "1"
}
dm = PlotlyLines([["y", "x"], ["y_away", "x_away"]], df,
labels=["position", "position_away"],
names=["Home", "Away"],
init_params=init_params,
layout={
"hovermode": "closest",
"plot_bgcolor": 'rgba(44,94,79,0.7)',
"xaxis": {"range": [0, 53]},
"paper_bgcolor": 'rgba(44, 94, 79, 0.0)',
})
ui.add_chart(dm)
imgs = Images(init_params, _onfield, _offfield)
ui.add_chart(imgs)
return ui
def make_nv_layout(filename):
# load the data
df = pd.read_csv(filename)
ui = UILayout("FilterChart")
# Make a button
choices = ["Heart Rate", "Pace", "Distance"]
btn = SelectButton("Data", choices, "Data", "Heart Rate")
ui.add_filter(btn)
# Add the chart
ui.add_chart(two_axis_focus(df))
ui.add_chart(pie_chart(df))
return ui
def make_nv_layout(filename):
# load the data
df = pd.read_csv(filename)
ui = UILayout("FilterChart")
# Make a button
choices = ["Heart Rate", "Pace", "Distance"]
btn = SelectButton("Data", choices, "Data", "Heart Rate")
ui.add_filter(btn)
# Add the chart
ui.add_chart(two_axis_focus(df))
ui.add_chart(pie_chart(df))
return ui
def make_nv_layout():
# load the data
filename = "../examples/nvd3/project/static/formatted_run.csv"
df = pd.read_csv(filename)
ui = UILayout("FilterChart")
# Make a button
choices = ["Heart Rate", "Pace", "Distance"]
btn = SelectButton("Data", choices, "Data", "Heart Rate")
ui.add_filter(btn)
# Add the chart
ui.add_chart(two_axis_focus(df))
ui.add_chart(pie_chart(df))
return ui
def make_nv_layout():
# load the data
filename = "../examples/nvd3/project/static/formatted_run.csv"
df = pd.read_csv(filename)
ui = UILayout("FilterChart")
# Make a button
choices = ["Heart Rate", "Pace", "Distance"]
btn = SelectButton("Data", choices, "Data", "Heart Rate")
ui.add_filter(btn)
# Add the chart
ui.add_chart(two_axis_focus(df))
ui.add_chart(pie_chart(df))
return ui
def make_datamaps_ui(filename):
# Make a UI
ui = UILayout("SimpleChart")
df = pd.read_csv(filename)
df.month = df.month.astype('str')
sldr = SliderInput("Month", 1, 13, "month", "1")
ui.add_filter(sldr)
dm = DatamapUSA("/data_map/",
"mapid",
df,
"state",
"color1",
init_params={"month": "1"})
ui.add_chart(dm)
return ui
def make_datamaps_ui():
# Make a UI
ui = UILayout("PyxleyChart")
datafile = "../examples/datamaps/project/Colorful_State.csv"
df = pd.read_csv(datafile)
df.month = df.month.astype('str')
sldr = SliderInput("Month", 1, 13, "month", "1")
ui.add_filter(sldr)
dm = DatamapUSA("/data_map/",
"mapid",
df,
"state",
"color1",
init_params={"month": "1"})
ui.add_chart(dm)
return ui
def make_ui(datafile):
# Make a UI
ui = UILayout("FilterChart", "pyxley", "component_id", filter_style="''")
df = pd.read_csv(datafile)
# Read in the data and stack it, so that we can filter on columns
sf = df.set_index("Date").stack().reset_index()
sf = sf.rename(columns={"level_1": "Data", 0: "value"})
# Make a Button
cols = [c for c in df.columns if c != "Date"]
btn = SelectButton("Data", cols, "Data", "Steps")
# Make a FilterFrame and add the button to the UI
ui.add_filter(btn)
dm = PlotlyLines([["Date", "value"]], sf, init_params={"Data": "Steps"})
ui.add_chart(dm)
return ui
def make_plotly_ui():
filename = "../examples/metricsgraphics/project/fitbit_data.csv"
df = pd.read_csv(filename)
# Make a UI
ui = UILayout("PyxleyChart")
# Read in the data and stack it, so that we can filter on columns
_stack = df.set_index("Date").stack().reset_index()
_stack = _stack.rename(columns={"level_1": "Data", 0: "value"})
# Make a Button
cols = [c for c in df.columns if c != "Date"]
btn = SelectButton("Data", cols, "Data", "Steps")
# add the button to the UI
ui.add_filter(btn)
init_params = {"Data": "Steps"}
def get_data():
args = {}
for c in init_params:
if request.args.get(c):
args[c] = request.args[c]
else:
args[c] = init_params[c]
return jsonify(
PlotlyAPI.line_plot(
PlotlyAPI.apply_filters(_stack, args),
[("Date", "value")],
"lines+markers",
{}
))
_plot = PlotlyAPI(
"plotly_chart",
"/api/plotly_line_plot/",
get_data,
init_params=init_params
)
ui.add_chart(_plot)
return ui
# Make a Button
btn = SelectButton("Persona", names, "persona", "Jim")
# Now make a FilterFrame for the histogram
hFig = Figure("/mghist/", "myhist")
hFig.layout.set_size(width=350, height=200)
hFig.layout.set_margin(left=0, right=0)
hFig.graphics.animate_on_load()
# Make a histogram
hc2 = Histogram(df_age, hFig, "age", 5, title="Customer Persona Age", init_params={"persona":"John"})
# Adding button and histogram to UI
ui.add_chart(hc2)
ui.add_filter(btn)
app = Flask(__name__)
sb = ui.render_layout(app, "./static/layout.js")
@app.route('/', methods=["GET"])
@app.route('/home', methods=["GET"])
def home():
return render_template("my_home.html")
@app.route('/point', methods=["GET"])
def point():
return render_template("get_point.html", title=TITLE)
"./jsx/custom",
"component_id")
# Read in the data and stack it, so that we can filter on columns
df = pd.read_csv("./project/static/formatted_run.csv")
# Make a Button
choices = ["Heart Rate", "Pace", "Distance"]
btn = SelectButton("Data", choices, "Data", "Heart Rate")
ui.add_filter(btn)
# Add our new chart
colors = ["#847c77", "#ff5c61"];
nc = NewChart("Seconds", "value", "Altitude", df,
init_params={"Data": "Heart Rate"}, colors=colors)
ui.add_chart(nc)
app = Flask(__name__)
sb = ui.render_layout(app, "./project/static/layout.js")
# Use the webpack file in the dir and bundle our javascript
from pyxley.utils import Webpack
wp = Webpack(".")
wp.run()
@app.route('/', methods=["GET"])
@app.route('/index', methods=["GET"])
def index():
_scripts = ["./bundle.js"]
return render_template('index.html',
title=TITLE,
# Make a Button
cols = [c for c in df.columns if c != "Date"]
btn = SelectButton("Data", cols, "Data", "Steps")
# Make a FilterFrame and add the button to the UI
ui.add_filter(btn)
# Make a Figure, add some settings, make a line plot
fig = Figure("/mgchart/", "mychart")
fig.graphics.transition_on_update(True)
fig.graphics.animate_on_load()
fig.layout.set_size(width=450, height=200)
fig.layout.set_margin(left=40, right=40)
lc = LineChart(sf, fig, "Date", ["value"], init_params={"Data": "Steps"}, timeseries=True)
ui.add_chart(lc)
# Now make a FilterFrame for the histogram
hFig = Figure("/mghist/", "myhist")
hFig.layout.set_size(width=450, height=200)
hFig.layout.set_margin(left=40, right=40)
hFig.graphics.animate_on_load()
# Make a histogram with 20 bins
hc = Histogram(sf, hFig, "value", 20, init_params={"Data": "Steps"})
ui.add_chart(hc)
# Let's play with our input
df["Date"] = pd.to_datetime(df["Date"])
df["week"] = df["Date"].apply(lambda x: x.isocalendar()[1])
gf = df.groupby("week").agg({
"Date": [np.min, np.max],
def make_table_layout(filename):
df = get_data(filename)
ui = UILayout("SimpleChart")
ui.add_chart(create_datatable(df))
return ui
def make_table_layout(filename):
df = get_data(filename)
ui = UILayout("SimpleChart")
ui.add_chart(create_datatable(df))
return ui
class MainView(MainModel):
def __init__(self, cache, save=False):
super(MainView, self).__init__(cache)
self.mod = Blueprint("main", __name__)
self.mod.add_url_rule("/", view_func=self.index)
self.ins_, self.static_ = get_static_folder()
self.init_params = {"play_index": "1"}
self.build_ui(save)
def index(self):
return render_template('index.html',
title="Main",
base_scripts=config.JS,
css=config.CSS,
page_scripts=["bundle.js"])
def build_ui(self, save):
self.ui = UILayout("FilterChart", "./jsx/SimpleChart", "component_id")
sldr = SliderInput("play_index", 1,
int(self.on_field["play_index"].max()),
"play_index", "1")
self.ui.add_filter(sldr)
# Add a plotly chart
self.ui.add_chart(add_plotly_chart(self.locations, self.init_params))
# Add the image panel
self.ui.add_chart(
add_image_panel(self.on_field, self.off_field, self.init_params))
if save:
self.ui.render_layout(self.mod,
self.static_ + "/layout.js",
alias="Main")
else:
self.ui.assign_routes(self.mod)
def check_args(self):
args = {}
for c in self.init_params:
if request.args.get(c):
args[c] = request.args[c]
else:
args[c] = self.init_params[c]
return args
def chart_data(self):
args = self.check_args()
df = PlotlyLines.apply_filters(self.locations, args)
return jsonify(
PlotlyLines.to_json(df, xypairs, mode, ptype, labels, layout,
names))
def image_data(self):
args = self.check_args()
_in = Images.apply_filters(self.on_field, args)
_out = Images.apply_filters(self.off_field, args)
return jsonify(Images.to_json(_in, _out, Images.imgs))
class MainView(MainModel):
def __init__(self, cache, save=False):
super(MainView, self).__init__(cache)
self.mod = Blueprint("main", __name__)
self.mod.add_url_rule("/", view_func=self.index)
self.ins_, self.static_ = get_static_folder()
self.init_params = {
"play_index": "1"
}
self.build_ui(save)
def index(self):
return render_template('index.html',
title="Main",
base_scripts=config.JS,
css=config.CSS,
page_scripts=["bundle.js"])
def build_ui(self, save):
self.ui = UILayout(
"FilterChart",
"./jsx/SimpleChart",
"component_id")
sldr = SliderInput("play_index", 1,
int(self.on_field["play_index"].max()),
"play_index", "1")
self.ui.add_filter(sldr)
# Add a plotly chart
self.ui.add_chart(
add_plotly_chart(self.locations, self.init_params)
)
# Add the image panel
self.ui.add_chart(
add_image_panel(self.on_field, self.off_field,
self.init_params)
)
if save:
self.ui.render_layout(self.mod,
self.static_ + "/layout.js",
alias="Main")
else:
self.ui.assign_routes(self.mod)
def check_args(self):
args = {}
for c in self.init_params:
if request.args.get(c):
args[c] = request.args[c]
else:
args[c] = self.init_params[c]
return args
def chart_data(self):
args = self.check_args()
df = PlotlyLines.apply_filters(
self.locations, args)
return jsonify(
PlotlyLines.to_json(
df,
xypairs,
mode,
ptype,
labels,
layout,
names
))
def image_data(self):
args = self.check_args()
_in = Images.apply_filters(self.on_field, args)
_out = Images.apply_filters(self.off_field, args)
return jsonify(
Images.to_json(
_in, _out, Images.imgs
))
def uploaded_file(filename):
extension = get_extension(filename)
path = os.path.join(app.config['UPLOAD_FOLDER'], extension, filename)
txt_path = os.path.join(app.config['UPLOAD_FOLDER'], 'txt', filename)
if extension == "pdf":
txt_path += '.txt'
if not os.path.isfile(txt_path):
#Layout preservation crucial to preserve clues about tabular data
cmd = "pdftotext -layout %s %s" % (path, txt_path)
os.system(cmd)
min_columns = request.args.get('min_columns')
tables = return_tables(txt_path)
#Construct histogram
lines_per_page = 80
nr_data_rows = []
for b, t in tables.iteritems():
e = t['end_line']
#print b, e
for l in range(b, e):
page = l / lines_per_page
if len(nr_data_rows) <= page:
nr_data_rows += ([0]*(page-len(nr_data_rows)+1))
nr_data_rows[page] += 1
dr = pd.DataFrame()
dr['value'] = nr_data_rows
dr['page'] = range(0, len(dr))
js_layout = filename+".js"
ui_show = UILayout(
"FilterChart",
"../static/bower_components/pyxley/build/pyxley.js",
"component_id",
filter_style="''")
if filename in all_charts:
print "old/update ui", filename
path_to_fig = '/show/line/'+filename
#del all_charts[filename]
#hFig = Figure(path_to_fig, "line")
#bc = LineChart(dr, hFig, "page", ["page"], "Rows containing Data per Page")
elif True:
print "new ui", filename
# Make a Button
cols = ["page"]
btn = SelectButton("Data", cols, "Data", "Data Rows per Page")
# Make a FilterFrame and add the button to the UI
ui_show.add_filter(btn)
# Now make a FilterFrame for the histogram
path_to_fig = '/show/line/'+filename
hFig = Figure(path_to_fig, "line")
hFig.layout.set_size(width=1000, height=300)
hFig.layout.set_margin(left=80, right=80)
#hFig.graphics.animate_on_load()
bc = LineChart(dr, hFig, "page", ["value"], "Rows containing Data per Page")
ui_show.add_chart(bc)
all_charts[filename] = bc
sb = ui_show.render_layout(app, "./static/ug/"+js_layout)
_scripts = ["ug/"+js_layout]
notices = ['Extraction Results for ' + filename, 'Ordered by lines']
dfs = (table_to_df(table).to_html() for table in tables.values())
headers = []
for t in tables.values():
if 'header' in t:
headers.append(t['header'])
else:
headers.append('-')
line_nrs = [('line %i-%i' % (t['begin_line'], t['end_line'])) for t in tables.values() ]
#headers = ['aslkdfjas', ' alsdkfjasoedf']
return render_template('index.html',
title=TITLE + ' - ' + filename,
base_scripts=scripts,
page_scripts=_scripts,
css=css, notices = notices, tables = dfs, headers=headers, line_nrs=line_nrs)
app = Flask(__name__)
# Make a Button
cols = [c for c in df.columns if c != "Date"]
btn = SelectButton("Data", cols, "Data", "Steps")
# Make a FilterFrame and add the button to the UI
ui.add_filter(btn)
# Make a Figure, add some settings, make a line plot
fig = Figure("/mgchart/", "mychart")
fig.graphics.transition_on_update(True)
fig.graphics.animate_on_load()
fig.layout.set_size(width=450, height=200)
fig.layout.set_margin(left=40, right=40)
lc = LineChart(sf, fig, "Date", ["value"], init_params={"Data": "Steps"}, timeseries=True)
ui.add_chart(lc)
sb = ui.render_layout(app, "./static/layout.js")
@app.route('/', methods=["GET"])
def index():
return render_template('index.html')
if __name__ == '__main__':
app.run()
def uploaded_file(filename):
extension = get_extension(filename)
path = os.path.join(app.config['UPLOAD_FOLDER'], extension, filename)
txt_path = os.path.join(app.config['UPLOAD_FOLDER'], 'txt', filename)
if extension == "pdf":
txt_path += '.txt'
if not os.path.isfile(txt_path):
#Layout preservation crucial to preserve clues about tabular data
cmd = "pdftotext -layout %s %s" % (path, txt_path)
os.system(cmd)
min_columns = request.args.get('min_columns')
tables = return_tables(txt_path)
#Construct histogram
lines_per_page = 80
nr_data_rows = []
for b, t in tables.iteritems():
e = t['end_line']
#print b, e
for l in range(b, e):
page = l / lines_per_page
if len(nr_data_rows) <= page:
nr_data_rows += ([0] * (page - len(nr_data_rows) + 1))
nr_data_rows[page] += 1
dr = pd.DataFrame()
dr['value'] = nr_data_rows
dr['page'] = range(0, len(dr))
js_layout = filename + ".js"
ui_show = UILayout("FilterChart",
"../static/bower_components/pyxley/build/pyxley.js",
"component_id",
filter_style="''")
if filename in all_charts:
print "old/update ui", filename
path_to_fig = '/show/line/' + filename
#del all_charts[filename]
#hFig = Figure(path_to_fig, "line")
#bc = LineChart(dr, hFig, "page", ["page"], "Rows containing Data per Page")
elif True:
print "new ui", filename
# Make a Button
cols = ["page"]
btn = SelectButton("Data", cols, "Data", "Data Rows per Page")
# Make a FilterFrame and add the button to the UI
ui_show.add_filter(btn)
# Now make a FilterFrame for the histogram
path_to_fig = '/show/line/' + filename
hFig = Figure(path_to_fig, "line")
hFig.layout.set_size(width=1000, height=300)
hFig.layout.set_margin(left=80, right=80)
#hFig.graphics.animate_on_load()
bc = LineChart(dr, hFig, "page", ["value"],
"Rows containing Data per Page")
ui_show.add_chart(bc)
all_charts[filename] = bc
sb = ui_show.render_layout(app, "./static/ug/" + js_layout)
_scripts = ["ug/" + js_layout]
notices = ['Extraction Results for ' + filename, 'Ordered by lines']
dfs = (table_to_df(table).to_html() for table in tables.values())
headers = []
for t in tables.values():
if 'header' in t:
headers.append(t['header'])
else:
headers.append('-')
line_nrs = [('line %i-%i' % (t['begin_line'], t['end_line']))
for t in tables.values()]
#headers = ['aslkdfjas', ' alsdkfjasoedf']
return render_template('index.html',
title=TITLE + ' - ' + filename,
base_scripts=scripts,
page_scripts=_scripts,
css=css,
notices=notices,
tables=dfs,
headers=headers,
line_nrs=line_nrs)
"component_id",
filter_style="''")
df = pd.read_csv("./static/Colorful_State.csv")
df.month = df.month.astype('str')
sldr = SliderInput("Month", 1, 13, "month", "1")
ui.add_filter(sldr)
dm = DatamapUSA("/data_map/",
"mapid",
df,
"state",
"color1",
init_params={"month": "1"})
ui.add_chart(dm)
app = Flask(__name__)
sb = ui.render_layout(app, "./static/layout.js")
@app.route('/', methods=["GET"])
@app.route('/index', methods=["GET"])
def index():
_scripts = ["./layout.js"]
return render_template('index.html',
title=TITLE,
base_scripts=scripts,
page_scripts=_scripts,
css=css)
# Make a Button
cols = [c for c in df.columns if c != "Date"]
btn = SelectButton("Data", cols, "Data", "Steps")
# Make a FilterFrame and add the button to the UI
ui.add_filter(btn)
# Make a Figure, add some settings, make a line plot
fig = Figure("/mgchart/", "mychart")
fig.graphics.transition_on_update(True)
fig.graphics.animate_on_load()
fig.layout.set_size(width=450, height=200)
fig.layout.set_margin(left=40, right=40)
lc = LineChart(sf, fig, "Date", ["value"], init_params={"Data": "Steps"}, timeseries=True)
ui.add_chart(lc)
# Now make a FilterFrame for the histogram
hFig = Figure("/mghist/", "myhist")
hFig.layout.set_size(width=450, height=200)
hFig.layout.set_margin(left=40, right=40)
hFig.graphics.animate_on_load()
# Make a histogram with 20 bins
hc = Histogram(sf, hFig, "value", 20, init_params={"Data": "Steps"})
ui.add_chart(hc)
# Let's play with our input
df["Date"] = pd.to_datetime(df["Date"])
df["week"] = df["Date"].apply(lambda x: x.isocalendar()[1])
gf = df.groupby("week").agg({
"Date": [np.min, np.max],
class MainView(MainModel):
_FILES = ["data"]
def __init__(self, cache, save=False):
super(MainView, self).__init__(cache)
self.mod = Blueprint("main", __name__)
self.mod.add_url_rule("/", view_func=self.index)
self.ins_, self.static_ = get_static_folder()
self.build_ui(save)
def index(self):
shims = {
"custom": ["twoAxisLinePlot", "pyxley"],
"main": ["custom"]
}
_module_list = [
["navbar", "main"]
]
_modules = OrderedDict([(",".join(m), m) for m in _module_list])
_baseUrl = "./static/js"
_paths = {
"pyxley": "../bower_components/pyxley/build/pyxley",
"main": "../layout"
}
return render_template('index.html',
title="Main",
base_scripts=config.JS,
css=config.CSS,
baseUrl=_baseUrl,
modules=_modules,
paths=json.dumps(_paths),
shims=json.dumps(shims))
def build_ui(self, save):
# Make a UI
self.ui = UILayout(
"RunLayout",
"custom",
"component_id")
choices = ["Heart Rate", "Pace", "Distance"]
btn = SelectButton("Data", choices, "Data", "Heart Rate")
self.ui.add_filter(btn)
"""
Add a download button,
I typically use this to trigger a download, but
it could be used to trigger another action
"""
dlbtn = DownloadButton("Download", "/download/", self.download)
self.ui.add_filter(dlbtn)
self.add_chart()
if save:
self.ui.render_layout(self.mod, self.static_ + "/layout.js")
else:
self.ui.assign_routes(self.mod)
def download(self):
print "Change this to do something else"
print "For now it will reload"
self.cache.load()
return jsonify({"data": "Success!"})
def chart_data(self):
args = {}
for c in self.init_params:
if request.args.get(c):
args[c] = request.args[c]
else:
args[c] = self.init_params[c]
return jsonify(NewChart.to_json(
NewChart.apply_filters(self.data, args),
"Seconds",
"value",
"Altitude"
))
def add_chart(self):
colors = ["#847c77", "#ff5c61"]
self.init_params = {
"Data": "Heart Rate"
}
nc = NewChart("Seconds", "value", "Altitude",
self.data,
init_params=self.init_params, colors=colors,
route_func=self.chart_data)
self.ui.add_chart(nc)
def make_mg_layout(filename):
# load a dataframe
df = pd.read_csv(filename)
# Make a UI
ui = UILayout("FilterChart")
# Make a Button
cols = [c for c in df.columns if c != "Year"]
btn = SelectButton("Abschlussprüfungsleistungen", cols, "Data",
"Abschlussprüfungsleistungen")
# add the button to the UI
ui.add_filter(btn)
# stack the dataframe
_stack = df.set_index("Year").stack().reset_index()
_stack = _stack.rename(columns={"level_1": "Data", 0: "value"})
# Make a Figure, add some settings, make a line plot
ui.add_chart(
create_line_plot(_stack,
i=0,
name="Abschlussprüfungsleistungen",
n=3,
titel="KPMG Umsätze"))
here = path.abspath(path.dirname(__file__))
df1 = pd.read_csv(here + "/file")
# Make a Button
cols1 = [c for c in df1.columns if c != "Year"]
btn1 = SelectButton("Professionals", cols1, "Data", "Professionals")
# add the button to the UI
ui.add_filter(btn1)
_stack1 = df1.set_index("Year").stack().reset_index()
_stack1 = _stack1.rename(columns={"level_1": "Data", 0: "value"})
# Make a Figure, add some settings, make a line plot
ui.add_chart(
create_line_plot(
_stack1,
i=1,
name="Professionals",
n=8,
titel="Employees of KPMG worldwide by position 2010-2017"))
# stack the dataframe
df2 = pd.read_csv(here + "/file1")
cols2 = [c for c in df2.columns if c != "Year"]
btn2 = SelectButton("Revenue in billion $", cols2, "Data",
"Revenue in billion $")
btn2.__setattr__("margin", 50)
ui.add_filter(btn2)
# Make a Button
_stack2 = df2.set_index("Year").stack().reset_index()
_stack2 = _stack2.rename(columns={"level_1": "Data", 0: "value"})
# Make a Figure, add some settings, make a line plot
ui.add_chart(
create_line_plot(
_stack2,
i=2,
name="Revenue in billion U.S. dollars",
n=6,
titel="Big data and business analytics revenue worldwide 2015-2020"
))
return ui
# Make a UI
ui = UILayout(
"FilterChart",
"pyxley",
"component_id",
filter_style="''")
df = pd.read_csv("./project/static/Colorful_State.csv")
df.month = df.month.astype('str')
sldr = SliderInput("Month", 1, 13, "month", "1")
ui.add_filter(sldr)
dm = DatamapUSA("/data_map/", "mapid", df, "state", "color1", init_params={"month": "1"})
ui.add_chart(dm)
app = Flask(__name__)
sb = ui.render_layout(app, "./project/static/layout.js")
# Create a webpack file and bundle our javascript
from pyxley.utils import Webpack
wp = Webpack(".")
wp.create_webpack_config(
"layout.js",
"./project/static/",
"bundle",
"./project/static/"
)
wp.run()