import matplotlib.pyplot as plt
plt.hist(x, cumulative=True, histtype='step')

import plotly.graph_objs as go
from plotly.offline import iplot
h = go.Histogram(x=x,
                         cumulative=dict(enabled=True),
                         marker=dict(color="rgba(0,0,0,0)",
                                     line=dict(color="red", width=1)))
iplot([h])

#imports
import plotly.plotly as py
import plotly.graph_objs as go
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot

import numpy as np
import pandas as pd

# qtconsole for debugginh
#%qtconsole -- style vim

# Notebook settings
init_notebook_mode(connected=True)

# Some sample data
x = np.random.normal(50, 5, 500)
binned = np.histogram(x, bins=25, density=True)
plot_y = np.cumsum(binned[0])

# Line
trace1 = go.Scatter(
    x=binned[1],
    y=plot_y,
    mode='lines',
    name="X",
    hoverinfo='all',
    line=dict(color = 'rgb(1255, 0, 0)', shape='hvh'
    )
)

data = [trace1]

# Layout
layout = dict(title = 'Binned data from normal distribution',
    legend=dict(
        y=0.5,
        traceorder='reversed',
        font=dict(
            size=16
        )
    )
)

# Make figure
fig = dict(data=data, layout=layout)

# Plot
iplot(fig, filename='line-shapes')