def process_pie():
df = process_input()
df[df.columns[1]] = pd.to_numeric(df[df.columns[1]])
df[df.columns[2]] = pd.to_numeric(df[df.columns[2]])
df[df.columns[3]] = pd.to_numeric(df[df.columns[3]])
col1 = df[df.columns[1]].values
col2 = df[df.columns[2]].values
col3 = df[df.columns[3]].values
Plotly.plot(document.getElementById('plot1'), [{
'values': [
df[df.columns[1]].sum(), df[df.columns[2]].sum(),
df[df.columns[3]].sum()
],
'labels': [
df[df.columns[1]].name, df[df.columns[2]].name,
df[df.columns[3]].name
],
'type':
'pie'
}], {
'height': 350,
'width': 500
})
def process_scatter():
df = process_input()
col1 = df[df.columns[0]].values
col2 = df[df.columns[1]].values
Plotly.plot(document.getElementById('plot2'),
[{
'x': col1,
'y': col2,
'type': 'scatter',
'mode': 'markers+lines',
'hoverinfo': 'label',
'label': 'Zoom Background Interest'
}])
def process_geo_map():
df = process_input()
df[df.columns[1]] = pd.to_numeric(df[df.columns[1]])
df[df.columns[2]] = pd.to_numeric(df[df.columns[2]])
col1 = df[df.columns[1]].values
col2 = df[df.columns[2]].values
col3 = df[df.columns[3]].values
Plotly.plot(document.getElementById('plot4'), [{
'type': 'scattergeo',
'lon': col2,
'lat': col1,
'text': col3
}])
def process_3d_maps():
df = process_input()
col0 = df[df.columns[0]].values
col1 = df[df.columns[1]].values
col2 = df[df.columns[2]].values
col3 = df[df.columns[3]].values
col4 = df[df.columns[4]].values
col5 = df[df.columns[5]].values
Plotly.plot(document.getElementById('plot6'), [{
'x': col0,
'y': col1,
'z': col2,
'mode': 'markers',
'marker': {
'size': 12,
'line': {
'color': 'rgba(217, 217, 217, 0.14)',
'width': 0.5
},
'opacity': 0.8
},
'type': 'scatter3d'
}, {
'x': col3,
'y': col4,
'z': col5,
'mode': 'markers',
'marker': {
'color': 'rgb(127, 127, 127)',
'size': 12,
'symbol': 'circle',
'line': {
'color': 'rgb(204, 204, 204)',
'width': 1
},
'opacity': 0.8
},
'type': 'scatter3d'
}], {'margin': {
'l': 0,
'r': 0,
'b': 0,
't': 0
}})
def process_heat_maps():
df = process_input()
df[df.columns[0]] = pd.to_numeric(df[df.columns[0]])
df[df.columns[1]] = pd.to_numeric(df[df.columns[1]])
df[df.columns[2]] = pd.to_numeric(df[df.columns[2]])
col0 = df[df.columns[0]].values
col1 = df[df.columns[1]].values
col2 = df[df.columns[2]].values
col3 = df[df.columns[3]].values
col4 = df[df.columns[4]].values
Plotly.plot(document.getElementById('plot5'), [{
'z': [col0, col1, col2],
'x': col3,
'y': col4,
'type': 'heatmap',
'hoverongaps': 'false'
}])
def process_time_series():
df = process_input()
df[df.columns[1]] = pd.to_numeric(df[df.columns[1]])
df[df.columns[2]] = pd.to_numeric(df[df.columns[2]])
df[df.columns[3]] = pd.to_numeric(df[df.columns[3]])
col1 = df[df.columns[0]].values
col2 = df[df.columns[1]].values
col3 = df[df.columns[2]].values
col4 = df[df.columns[3]].values
Plotly.plot(document.getElementById('plot3'), [{
'x': col1,
'y': col2,
'type': 'scatter',
'mode': "lines",
'name': 'Pho',
'line': {
'color': '#17BECF'
}
}, {
'x': col1,
'y': col3,
'type': "scatter",
'mode': "lines",
'name': 'Ramen',
'line': {
'color': '#7F7F7F'
}
}, {
'x': col1,
'y': col4,
'type': "scatter",
'mode': "lines",
'name': 'Soba',
'line': {
'color': '#7C19E2'
}
}])