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first pass on time-series notebook
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‎notebooks/time-series.md

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title: Time Series Plots | plotly
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---
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#### New to Plotly?
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Plotly's Python library is free and open source! [Get started](https://plot.ly/python/getting-started/) by downloading the client and [reading the primer](https://plot.ly/python/getting-started/).
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<br>You can set up Plotly to work in [online](https://plot.ly/python/getting-started/#initialization-for-online-plotting) or [offline](https://plot.ly/python/getting-started/#initialization-for-offline-plotting) mode, or in [jupyter notebooks](https://plot.ly/python/getting-started/#start-plotting-online).
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<br>We also have a quick-reference [cheatsheet](https://images.plot.ly/plotly-documentation/images/python_cheat_sheet.pdf) (new!) to help you get started!
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```python
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from _plotly_future_ import v4
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```
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### Time Series Plot with `datetime` Objects ###
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Time series can be represented using either `plotly_express` functions (`px.line`, `px.scatter`) or `plotly.graph_objs` charts objects (`go.Scatter`). For more examples of such charts, see the documentation of [line and scatter plots](https://plot.ly/python/line-and-scatter/).
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```python
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import plotly.plotly as py
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import plotly.graph_objs as go
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# Using plotly_express
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import plotly_express as px
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import pandas as pd
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from datetime import datetime
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df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')
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data = [go.Scatter(x=df.Date, y=df['AAPL.High'])]
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py.iplot(data, filename = 'time-series-simple')
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fig = px.line(df, x='Date', y='AAPL.High')
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fig.show()
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```
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### Date Strings
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```python
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import plotly.plotly as py
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# Using graph_objs
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import plotly.graph_objs as go
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import pandas as pd
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df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')
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df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv")
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data = [go.Scatter(
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x=df.Date,
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y=df['AAPL.Close'])]
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py.iplot(data)
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fig = go.Figure([go.Scatter(x=df['Date'], y=df['AAPL.High'])])
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fig.show()
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```
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### Time Series Plot with Custom Date Range
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The data range can be set manually using either `datetime.datetime` objects, or date strings.
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```python
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import plotly.plotly as py
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import plotly.graph_objs as go
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import datetime
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def to_unix_time(dt):
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epoch = datetime.datetime.utcfromtimestamp(0)
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return (dt - epoch).total_seconds() * 1000
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x = [datetime.datetime(year=2013, month=10, day=04),
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datetime.datetime(year=2013, month=11, day=05),
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datetime.datetime(year=2013, month=12, day=06)]
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data = [go.Scatter(
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x=x,
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y=[1, 3, 6])]
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x = [datetime.datetime(year=2013, month=10, day=4),
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datetime.datetime(year=2013, month=11, day=5),
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datetime.datetime(year=2013, month=12, day=6)]
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data = [go.Scatter(x=x, y=[1, 3, 6])]
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layout = go.Layout(xaxis = dict(
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range = [to_unix_time(datetime.datetime(2013, 10, 17)),
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to_unix_time(datetime.datetime(2013, 11, 20))]
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))
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fig = go.Figure(data = data, layout = layout)
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py.iplot(fig)
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fig = go.Figure(data=data)
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# Use datetime objects to set xaxis range
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fig.update(layout_xaxis_range=[datetime.datetime(2013, 10, 17),
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datetime.datetime(2013, 11, 20)])
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```
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### Manually Set Range
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```python
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import plotly.plotly as py
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import plotly.graph_objs as go
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import pandas as pd
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df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv")
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trace_high = go.Scatter(
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x=df.Date,
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y=df['AAPL.High'],
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name = "AAPL High",
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line = dict(color = '#17BECF'),
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opacity = 0.8)
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name="AAPL High",
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line_color='deepskyblue',
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opacity=0.8)
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trace_low = go.Scatter(
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x=df.Date,
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y=df['AAPL.Low'],
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name = "AAPL Low",
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line = dict(color = '#7F7F7F'),
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opacity = 0.8)
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data = [trace_high,trace_low]
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layout = dict(
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title = "Manually Set Date Range",
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xaxis = dict(
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range = ['2016-07-01','2016-12-31'])
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)
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fig = dict(data=data, layout=layout)
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py.iplot(fig, filename = "Manually Set Range")
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name="AAPL Low",
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line_color='dimgray',
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opacity=0.8)
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fig = go.Figure(data=[trace_high, trace_low])
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# Use date string to set xaxis range
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fig.update(layout_xaxis_range=['2016-07-01','2016-12-31'],
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layout_title_text="Manually Set Date Range")
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fig.show()
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```
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### Time Series With Rangeslider
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```python
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import plotly.plotly as py
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import plotly.graph_objs as go
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import pandas as pd
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df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv")
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trace_high = go.Scatter(
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x=df.Date,
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y=df['AAPL.High'],
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name = "AAPL High",
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line = dict(color = '#17BECF'),
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opacity = 0.8)
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name="AAPL High",
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line_color='deepskyblue')
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trace_low = go.Scatter(
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x=df.Date,
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y=df['AAPL.Low'],
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name = "AAPL Low",
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line = dict(color = '#7F7F7F'),
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opacity = 0.8)
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data = [trace_high,trace_low]
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layout = dict(
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title='Time Series with Rangeslider',
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xaxis=dict(
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rangeselector=dict(
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buttons=list([
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dict(count=1,
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label='1m',
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step='month',
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stepmode='backward'),
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dict(count=6,
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label='6m',
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step='month',
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stepmode='backward'),
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dict(step='all')
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])
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),
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rangeslider=dict(
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visible = True
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),
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type='date'
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)
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)
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fig = dict(data=data, layout=layout)
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py.iplot(fig, filename = "Time Series with Rangeslider")
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name="AAPL Low",
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line_color='dimgray')
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fig = go.Figure(data=[trace_high, trace_low])
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fig.update(layout_title_text='Time Series with Rangeslider',
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layout_xaxis_rangeslider_visible=True)
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fig.show()
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```
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### Dash Example
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#### Reference
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See https://plot.ly/python/reference/#layout-xaxis-rangeslider and<br> https://plot.ly/python/reference/#layout-xaxis-rangeselector for more information and chart attribute options!
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```python
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from IPython.display import display, HTML
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display(HTML('<link href="//fonts.googleapis.com/css?family=Open+Sans:600,400,300,200|Inconsolata|Ubuntu+Mono:400,700" rel="stylesheet" type="text/css" />'))
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display(HTML('<link rel="stylesheet" type="text/css" href="http://help.plot.ly/documentation/all_static/css/ipython-notebook-custom.css">'))
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!pip install git+https://github.com/plotly/publisher.git --upgrade
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import publisher
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publisher.publish(
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'time-series.ipynb', 'python/time-series/', 'Python Time Series | Examples | Plotly',
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'How to plot date and time in python. ',
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title= 'Time Series Plots | plotly',
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name = 'Time Series',
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has_thumbnail='true', thumbnail='thumbnail/time-series.jpg',
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language='python', page_type='example_index',
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display_as='financial', order=0,
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ipynb='~notebook_demo/213')
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```

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