Fix FF docs.

Author: theengineear

plotly/figure_factory/_2d_density.py

@@ -45,7 +45,7 @@ def create_2d_density(x, y, colorscale='Earth', ncontours=20,
     Example 1: Simple 2D Density Plot
     ```
     import plotly.plotly as py
-    from plotly.tools import FigureFactory as FF
+    from plotly.figure_factory create_2d_density
 
     import numpy as np
 
@@ -55,7 +55,7 @@ def create_2d_density(x, y, colorscale='Earth', ncontours=20,
     y = (t**6)+(0.3*np.random.randn(2000))
 
     # Create a figure
-    fig = FF.create_2D_density(x, y)
+    fig = create_2D_density(x, y)
 
     # Plot the data
     py.iplot(fig, filename='simple-2d-density')
@@ -64,7 +64,7 @@ def create_2d_density(x, y, colorscale='Earth', ncontours=20,
     Example 2: Using Parameters
     ```
     import plotly.plotly as py
-    from plotly.tools import FigureFactory as FF
+    from plotly.figure_factory create_2d_density
 
     import numpy as np
 
@@ -78,7 +78,7 @@ def create_2d_density(x, y, colorscale='Earth', ncontours=20,
                   (1, 1, 0.2), (0.98,0.98,0.98)]
 
     # Create a figure
-    fig = FF.create_2D_density(
+    fig = create_2D_density(
         x, y, colorscale=colorscale,
         hist_color='rgb(255, 237, 222)', point_size=3)
 

plotly/figure_factory/_annotated_heatmap.py

@@ -72,14 +72,14 @@ def create_annotated_heatmap(z, x=None, y=None, annotation_text=None,
     Example 1: Simple annotated heatmap with default configuration
     ```
     import plotly.plotly as py
-    from plotly.tools import FigureFactory as FF
+    from plotly.figure_factory create_annotated_heatmap
 
     z = [[0.300000, 0.00000, 0.65, 0.300000],
          [1, 0.100005, 0.45, 0.4300],
          [0.300000, 0.00000, 0.65, 0.300000],
          [1, 0.100005, 0.45, 0.00000]]
 
-    figure = FF.create_annotated_heatmap(z)
+    figure = create_annotated_heatmap(z)
     py.iplot(figure)
     ```
     """

plotly/figure_factory/_candlestick.py

@@ -117,19 +117,19 @@ def create_candlestick(open, high, low, close, dates=None, direction='both',
     Example 1: Simple candlestick chart from a Pandas DataFrame
     ```
     import plotly.plotly as py
-    from plotly.tools import FigureFactory as FF
+    from plotly.figure_factory import create_candlestick
     from datetime import datetime
 
     import pandas.io.data as web
 
     df = web.DataReader("aapl", 'yahoo', datetime(2007, 10, 1), datetime(2009, 4, 1))
-    fig = FF.create_candlestick(df.Open, df.High, df.Low, df.Close, dates=df.index)
+    fig = create_candlestick(df.Open, df.High, df.Low, df.Close, dates=df.index)
     py.plot(fig, filename='finance/aapl-candlestick', validate=False)
     ```
 
     Example 2: Add text and annotations to the candlestick chart
     ```
-    fig = FF.create_candlestick(df.Open, df.High, df.Low, df.Close, dates=df.index)
+    fig = create_candlestick(df.Open, df.High, df.Low, df.Close, dates=df.index)
     # Update the fig - all options here: https://plot.ly/python/reference/#Layout
     fig['layout'].update({
         'title': 'The Great Recession',
@@ -151,7 +151,7 @@ def create_candlestick(open, high, low, close, dates=None, direction='both',
     Example 3: Customize the candlestick colors
     ```
     import plotly.plotly as py
-    from plotly.tools import FigureFactory as FF
+    from plotly.figure_factory import create_candlestick
     from plotly.graph_objs import Line, Marker
     from datetime import datetime
 
@@ -160,13 +160,13 @@ def create_candlestick(open, high, low, close, dates=None, direction='both',
     df = web.DataReader("aapl", 'yahoo', datetime(2008, 1, 1), datetime(2009, 4, 1))
 
     # Make increasing candlesticks and customize their color and name
-    fig_increasing = FF.create_candlestick(df.Open, df.High, df.Low, df.Close, dates=df.index,
+    fig_increasing = create_candlestick(df.Open, df.High, df.Low, df.Close, dates=df.index,
         direction='increasing', name='AAPL',
         marker=Marker(color='rgb(150, 200, 250)'),
         line=Line(color='rgb(150, 200, 250)'))
 
     # Make decreasing candlesticks and customize their color and name
-    fig_decreasing = FF.create_candlestick(df.Open, df.High, df.Low, df.Close, dates=df.index,
+    fig_decreasing = create_candlestick(df.Open, df.High, df.Low, df.Close, dates=df.index,
         direction='decreasing',
         marker=Marker(color='rgb(128, 128, 128)'),
         line=Line(color='rgb(128, 128, 128)'))
@@ -183,7 +183,7 @@ def create_candlestick(open, high, low, close, dates=None, direction='both',
     Example 4: Candlestick chart with datetime objects
     ```
     import plotly.plotly as py
-    from plotly.tools import FigureFactory as FF
+    from plotly.figure_factory import create_candlestick
 
     from datetime import datetime
 
@@ -199,7 +199,7 @@ def create_candlestick(open, high, low, close, dates=None, direction='both',
              datetime(year=2014, month=2, day=10)]
 
     # Create ohlc
-    fig = FF.create_candlestick(open_data, high_data,
+    fig = create_candlestick(open_data, high_data,
         low_data, close_data, dates=dates)
 
     py.iplot(fig, filename='finance/simple-candlestick', validate=False)

plotly/figure_factory/_dendrogram.py

@@ -41,26 +41,26 @@ def create_dendrogram(X, orientation="bottom", labels=None,
     Example 1: Simple bottom oriented dendrogram
     ```
     import plotly.plotly as py
-    from plotly.tools import FigureFactory as FF
+    from plotly.figure_factory import create_dendrogram
 
     import numpy as np
 
     X = np.random.rand(10,10)
-    dendro = FF.create_dendrogram(X)
+    dendro = create_dendrogram(X)
     plot_url = py.plot(dendro, filename='simple-dendrogram')
 
     ```
 
     Example 2: Dendrogram to put on the left of the heatmap
     ```
     import plotly.plotly as py
-    from plotly.tools import FigureFactory as FF
+    from plotly.figure_factory import create_dendrogram
 
     import numpy as np
 
     X = np.random.rand(5,5)
     names = ['Jack', 'Oxana', 'John', 'Chelsea', 'Mark']
-    dendro = FF.create_dendrogram(X, orientation='right', labels=names)
+    dendro = create_dendrogram(X, orientation='right', labels=names)
     dendro['layout'].update({'width':700, 'height':500})
 
     py.iplot(dendro, filename='vertical-dendrogram')
@@ -69,14 +69,14 @@ def create_dendrogram(X, orientation="bottom", labels=None,
     Example 3: Dendrogram with Pandas
     ```
     import plotly.plotly as py
-    from plotly.tools import FigureFactory as FF
+    from plotly.figure_factory import create_dendrogram
 
     import numpy as np
     import pandas as pd
 
     Index= ['A','B','C','D','E','F','G','H','I','J']
     df = pd.DataFrame(abs(np.random.randn(10, 10)), index=Index)
-    fig = FF.create_dendrogram(df, labels=Index)
+    fig = create_dendrogram(df, labels=Index)
     url = py.plot(fig, filename='pandas-dendrogram')
     ```
     """

plotly/figure_factory/_distplot.py

@@ -80,7 +80,7 @@ def create_distplot(hist_data, group_labels, bin_size=1., curve_type='kde',
     Example 1: Simple distplot of 1 data set
     ```
     import plotly.plotly as py
-    from plotly.tools import FigureFactory as FF
+    from plotly.figure_factory import create_distplot
 
     hist_data = [[1.1, 1.1, 2.5, 3.0, 3.5,
                   3.5, 4.1, 4.4, 4.5, 4.5,
@@ -89,15 +89,15 @@ def create_distplot(hist_data, group_labels, bin_size=1., curve_type='kde',
 
     group_labels = ['distplot example']
 
-    fig = FF.create_distplot(hist_data, group_labels)
+    fig = create_distplot(hist_data, group_labels)
 
     url = py.plot(fig, filename='Simple distplot', validate=False)
     ```
 
     Example 2: Two data sets and added rug text
     ```
     import plotly.plotly as py
-    from plotly.tools import FigureFactory as FF
+    from plotly.figure_factory import create_distplot
 
     # Add histogram data
     hist1_x = [0.8, 1.2, 0.2, 0.6, 1.6,
@@ -125,7 +125,7 @@ def create_distplot(hist_data, group_labels, bin_size=1., curve_type='kde',
     rug_text_all = [rug_text_1, rug_text_2]
 
     # Create distplot
-    fig = FF.create_distplot(
+    fig = create_distplot(
         hist_data, group_labels, rug_text=rug_text_all, bin_size=.2)
 
     # Add title
@@ -138,7 +138,7 @@ def create_distplot(hist_data, group_labels, bin_size=1., curve_type='kde',
     Example 3: Plot with normal curve and hide rug plot
     ```
     import plotly.plotly as py
-    from plotly.tools import FigureFactory as FF
+    from plotly.figure_factory import create_distplot
     import numpy as np
 
     x1 = np.random.randn(190)
@@ -149,7 +149,7 @@ def create_distplot(hist_data, group_labels, bin_size=1., curve_type='kde',
     hist_data = [x1, x2, x3, x4]
     group_labels = ['2012', '2013', '2014', '2015']
 
-    fig = FF.create_distplot(
+    fig = create_distplot(
         hist_data, group_labels, curve_type='normal',
         show_rug=False, bin_size=.4)
 
@@ -158,15 +158,15 @@ def create_distplot(hist_data, group_labels, bin_size=1., curve_type='kde',
     Example 4: Distplot with Pandas
     ```
     import plotly.plotly as py
-    from plotly.tools import FigureFactory as FF
+    from plotly.figure_factory import create_distplot
     import numpy as np
     import pandas as pd
 
     df = pd.DataFrame({'2012': np.random.randn(200),
                        '2013': np.random.randn(200)+1})
-    py.iplot(FF.create_distplot([df[c] for c in df.columns], df.columns),
-                                filename='examples/distplot with pandas',
-                                validate=False)
+    py.iplot(create_distplot([df[c] for c in df.columns], df.columns),
+                             filename='examples/distplot with pandas',
+                             validate=False)
     ```
     """
     validate_distplot(hist_data, curve_type)

plotly/figure_factory/_gantt.py

@@ -621,15 +621,15 @@ def create_gantt(df, colors=None, index_col=None, show_colorbar=False,
     Example 1: Simple Gantt Chart
     ```
     import plotly.plotly as py
-    from plotly.tools import FigureFactory as FF
+    from plotly.figure_factory import create_gantt
 
     # Make data for chart
     df = [dict(Task="Job A", Start='2009-01-01', Finish='2009-02-30'),
           dict(Task="Job B", Start='2009-03-05', Finish='2009-04-15'),
           dict(Task="Job C", Start='2009-02-20', Finish='2009-05-30')]
 
     # Create a figure
-    fig = FF.create_gantt(df)
+    fig = create_gantt(df)
 
     # Plot the data
     py.iplot(fig, filename='Simple Gantt Chart', world_readable=True)
@@ -638,7 +638,7 @@ def create_gantt(df, colors=None, index_col=None, show_colorbar=False,
     Example 2: Index by Column with Numerical Entries
     ```
     import plotly.plotly as py
-    from plotly.tools import FigureFactory as FF
+    from plotly.figure_factory import create_gantt
 
     # Make data for chart
     df = [dict(Task="Job A", Start='2009-01-01',
@@ -649,9 +649,9 @@ def create_gantt(df, colors=None, index_col=None, show_colorbar=False,
                Finish='2009-05-30', Complete=95)]
 
     # Create a figure with Plotly colorscale
-    fig = FF.create_gantt(df, colors='Blues', index_col='Complete',
-                          show_colorbar=True, bar_width=0.5,
-                          showgrid_x=True, showgrid_y=True)
+    fig = create_gantt(df, colors='Blues', index_col='Complete',
+                       show_colorbar=True, bar_width=0.5,
+                       showgrid_x=True, showgrid_y=True)
 
     # Plot the data
     py.iplot(fig, filename='Numerical Entries', world_readable=True)
@@ -660,7 +660,7 @@ def create_gantt(df, colors=None, index_col=None, show_colorbar=False,
     Example 3: Index by Column with String Entries
     ```
     import plotly.plotly as py
-    from plotly.tools import FigureFactory as FF
+    from plotly.figure_factory import create_gantt
 
     # Make data for chart
     df = [dict(Task="Job A", Start='2009-01-01',
@@ -671,12 +671,9 @@ def create_gantt(df, colors=None, index_col=None, show_colorbar=False,
                Finish='2009-05-30', Resource='Banana')]
 
     # Create a figure with Plotly colorscale
-    fig = FF.create_gantt(df, colors=['rgb(200, 50, 25)',
-                                      (1, 0, 1),
-                                      '#6c4774'],
-                          index_col='Resource',
-                          reverse_colors=True,
-                          show_colorbar=True)
+    fig = create_gantt(df, colors=['rgb(200, 50, 25)', (1, 0, 1), '#6c4774'],
+                       index_col='Resource', reverse_colors=True,
+                       show_colorbar=True)
 
     # Plot the data
     py.iplot(fig, filename='String Entries', world_readable=True)
@@ -685,7 +682,7 @@ def create_gantt(df, colors=None, index_col=None, show_colorbar=False,
     Example 4: Use a dictionary for colors
     ```
     import plotly.plotly as py
-    from plotly.tools import FigureFactory as FF
+    from plotly.figure_factory import create_gantt
 
     # Make data for chart
     df = [dict(Task="Job A", Start='2009-01-01',
@@ -701,9 +698,8 @@ def create_gantt(df, colors=None, index_col=None, show_colorbar=False,
               'Banana': (1, 1, 0.2)}
 
     # Create a figure with Plotly colorscale
-    fig = FF.create_gantt(df, colors=colors,
-                          index_col='Resource',
-                          show_colorbar=True)
+    fig = create_gantt(df, colors=colors, index_col='Resource',
+                       show_colorbar=True)
 
     # Plot the data
     py.iplot(fig, filename='dictioanry colors', world_readable=True)
@@ -712,7 +708,7 @@ def create_gantt(df, colors=None, index_col=None, show_colorbar=False,
     Example 5: Use a pandas dataframe
     ```
     import plotly.plotly as py
-    from plotly.tools import FigureFactory as FF
+    from plotly.figure_factory import create_gantt
 
     import pandas as pd
 
@@ -723,9 +719,9 @@ def create_gantt(df, colors=None, index_col=None, show_colorbar=False,
                       columns=['Task', 'Start', 'Finish', 'Complete'])
 
     # Create a figure with Plotly colorscale
-    fig = FF.create_gantt(df, colors='Blues', index_col='Complete',
-                          show_colorbar=True, bar_width=0.5,
-                          showgrid_x=True, showgrid_y=True)
+    fig = create_gantt(df, colors='Blues', index_col='Complete',
+                       show_colorbar=True, bar_width=0.5,
+                       showgrid_x=True, showgrid_y=True)
 
     # Plot the data
     py.iplot(fig, filename='data with dataframe', world_readable=True)