Reports
Examples & Tutorials
Tables, Data and Big Numbers
Datapane has various blocks for adding datasets to your reports, from simple tables to interactive drilldowns.
Table
The Table component takes a pandas DataFrame and renders an HTML table in your report.
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import datapane as dp
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import pandas as pd
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import numpy as np
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df = pd.DataFrame({
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'A': np.random.normal(-1, 1, 5),
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'B': np.random.normal(1, 2, 5),
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})
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table = dp.Table(df)
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report = dp.Report(table)
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report.upload(name='sample_table')
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If your DataFrame includes DataFrame Styles, these will be included in your report. DataFrame styles allows you create custom formatted tables; for instance, to show trends, highlight cells, add bar charts, or display correlations.
Table is the best option for displaying multidimensional DataFrames, as
DataTable will flatten your data.DataTable
The DataTable block takes a pandas DataFrame and renders an interactive, sortable, searchable table in your report, along with advanced analysis options such as exploring data through SandDance. It supports large datasets and viewers can also download the table from the website as a CSV or Excel file.
DataTable works for reports uploaded to Datapane.com as well as locally saved reports.
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import datapane as dp
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import pandas as pd
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import numpy as np
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df = pd.DataFrame({
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'A': np.random.normal(-1, 1, 5000),
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'B': np.random.normal(1, 2, 5000),
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})
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table = dp.DataTable(df)
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report = dp.Report(table)
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report.upload(name='sample_table')
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Running Queries on DataTable
You can run SQL queries on your datatable if you need more advanced filtering & calculations. In the previous example, if we wanted to show only the rows which had a value A > 0.5, we would write the following (note that
$tbl is the builtin table name and cannot be changed): 1
SELECT * FROM $tbl
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WHERE A > 0.5
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Python Dictionary & JSON
To include Python objects and JSON, we recommend using the
File block.
Big Number
A single number or change can often be the most important thing in a report. The
BigNumbercomponent allows you to present KPIs, changes, and statistics in a friendly way to your viewers. You can optionally set intent, and pass in numbers or text. Python
Text Report
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import datapane as dp
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dp.Report(
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dp.Group(columns=2,
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dp.BigNumber(
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heading="Number of percentage points",
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value="84%",
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change="2%",
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is_upward_change=True
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),
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dp.BigNumber(
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heading="Simple Statistic",
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value=100
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)
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)
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).upload(name="sample_bignum")
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```datapane
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block: Group
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columns: 2
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blocks:
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- block: BigNumber
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heading: Number of percentage points
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value: 84%
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change: 2%
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is_upward_change: True
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- block: BigNumber
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heading: Simple Statistic
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value: 100
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```
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Last modified 3mo ago
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