It is a plugin to pyexcel and extends its capbility to present and write data in text fromats mainly through tabulate:
Since v0.2.7, json and ndjson input are also supported.
>>> import pyexcel as pe
>>> sheet = pe.Sheet()
>>> sheet.json = '[[1,2],[2,3]]'
>>> sheet
pyexcel sheet:
+---+---+
| 1 | 2 |
+---+---+
| 2 | 3 |
+---+---+
>>> highspeedrail = pe.Sheet()
>>> highspeedrail.json = """
... [{"year": 1903, "country": "Germany", "speed": "206.7km/h"},
... {"year": 1964, "country": "Japan", "speed": "210km/h"},
... {"year": 2008, "country": "China", "speed": "350km/h"}]
... """
>>> highspeedrail.name = 'High Speed Train Speed Break Through (Source: Wikipedia)'
>>> highspeedrail
High Speed Train Speed Break Through (Source: Wikipedia):
+---------+-----------+------+
| country | speed | year |
+---------+-----------+------+
| Germany | 206.7km/h | 1903 |
+---------+-----------+------+
| Japan | 210km/h | 1964 |
+---------+-----------+------+
| China | 350km/h | 2008 |
+---------+-----------+------+
>>> henley_on_thames_facts = pe.Sheet()
>>> henley_on_thames_facts.json = """
... {"area": "5.58 square meters",
... "population": "11,619",
... "civial parish": "Henley-on-Thames",
... "latitude": "51.536",
... "longitude": "-0.898"
... }"""
>>> henley_on_thames_facts
pyexcel sheet:
+--------------------+------------------+----------+-----------+------------+
| area | civial parish | latitude | longitude | population |
+--------------------+------------------+----------+-----------+------------+
| 5.58 square meters | Henley-on-Thames | 51.536 | -0.898 | 11,619 |
+--------------------+------------------+----------+-----------+------------+
>>> ccs_insight = pe.Sheet()
>>> ccs_insight.name = "Worldwide Mobile Phone Shipments (Billions), 2017-2021"
>>> ccs_insight.json = """
... {"year": ["2017", "2018", "2019", "2020", "2021"],
... "smart phones": [1.53, 1.64, 1.74, 1.82, 1.90],
... "feature phones": [0.46, 0.38, 0.30, 0.23, 0.17]}"""
>>> ccs_insight
pyexcel sheet:
+----------------+--------------+------+
| feature phones | smart phones | year |
+----------------+--------------+------+
| 0.46 | 1.53 | 2017 |
+----------------+--------------+------+
| 0.38 | 1.64 | 2018 |
+----------------+--------------+------+
| 0.3 | 1.74 | 2019 |
+----------------+--------------+------+
| 0.23 | 1.82 | 2020 |
+----------------+--------------+------+
| 0.17 | 1.9 | 2021 |
+----------------+--------------+------+
Here is a variant of json:
>>> highspeedrail2 = pe.Sheet()
>>> highspeedrail2.ndjson = """
... {"year": 1903, "country": "Germany", "speed": "206.7km/h"}
... {"year": 1964, "country": "Japan", "speed": "210km/h"}
... {"year": 2008, "country": "China", "speed": "350km/h"}
... """.strip()
>>> highspeedrail2.name = 'High Speed Train Speed Break Through (Source: Wikipedia)'
>>> highspeedrail2
High Speed Train Speed Break Through (Source: Wikipedia):
+---------+-----------+------+
| country | speed | year |
+---------+-----------+------+
| Germany | 206.7km/h | 1903 |
+---------+-----------+------+
| Japan | 210km/h | 1964 |
+---------+-----------+------+
| China | 350km/h | 2008 |
+---------+-----------+------+
>>> henley_on_thames_facts2 = pe.Sheet()
>>> henley_on_thames_facts2.ndjson = """
... {"area": "5.58 square meters"}
... {"population": "11,619"}
... {"civial parish": "Henley-on-Thames"}
... {"latitude": "51.536"}
... {"longitude": "-0.898"}
... """.strip()
>>> henley_on_thames_facts2
pyexcel sheet:
+---------------+--------------------+
| area | 5.58 square meters |
+---------------+--------------------+
| population | 11,619 |
+---------------+--------------------+
| civial parish | Henley-on-Thames |
+---------------+--------------------+
| latitude | 51.536 |
+---------------+--------------------+
| longitude | -0.898 |
+---------------+--------------------+
>>> ccs_insight2 = pe.Sheet()
>>> ccs_insight2.name = "Worldwide Mobile Phone Shipments (Billions), 2017-2021"
>>> ccs_insight2.ndjson = """
... {"year": ["2017", "2018", "2019", "2020", "2021"]}
... {"smart phones": [1.53, 1.64, 1.74, 1.82, 1.90]}
... {"feature phones": [0.46, 0.38, 0.30, 0.23, 0.17]}
... """.strip()
>>> ccs_insight2
pyexcel sheet:
+----------------+------+------+------+------+------+
| year | 2017 | 2018 | 2019 | 2020 | 2021 |
+----------------+------+------+------+------+------+
| smart phones | 1.53 | 1.64 | 1.74 | 1.82 | 1.9 |
+----------------+------+------+------+------+------+
| feature phones | 0.46 | 0.38 | 0.3 | 0.23 | 0.17 |
+----------------+------+------+------+------+------+
>>> import pyexcel as pe
>>> content = [
... ["Column 1", "Column 2", "Column 3"],
... [1, 2, 3],
... [4, 5, 6],
... [7, 8, 9]
... ]
>>> sheet = pe.Sheet(content)
>>> print(sheet.simple)
pyexcel sheet:
-------- -------- --------
Column 1 Column 2 Column 3
1 2 3
4 5 6
7 8 9
-------- -------- --------
>>> sheet.name_columns_by_row(0)
>>> print(sheet.simple)
pyexcel sheet:
Column 1 Column 2 Column 3
---------- ---------- ----------
1 2 3
4 5 6
7 8 9
>>> print(sheet.grid) pyexcel sheet: +------------+------------+------------+ | Column 1 | Column 2 | Column 3 | +============+============+============+ | 1 | 2 | 3 | +------------+------------+------------+ | 4 | 5 | 6 | +------------+------------+------------+ | 7 | 8 | 9 | +------------+------------+------------+
>>> multiple_sheets = {
... 'Sheet 1':
... [
... [1.0, 2.0, 3.0],
... [4.0, 5.0, 6.0],
... [7.0, 8.0, 9.0]
... ],
... 'Sheet 2':
... [
... ['X', 'Y', 'Z'],
... [1.0, 2.0, 3.0],
... [4.0, 5.0, 6.0]
... ],
... 'Sheet 3':
... [
... ['O', 'P', 'Q'],
... [3.0, 2.0, 1.0],
... [4.0, 3.0, 2.0]
... ]
... }
>>> book = pe.Book(multiple_sheets)
>>> book.save_as("myfile.mediawiki")
>>> myfile = open("myfile.mediawiki")
>>> print(myfile.read())
Sheet 1:
{| class="wikitable" style="text-align: left;"
|+ <!-- caption -->
|-
| align="right"| 1 || align="right"| 2 || align="right"| 3
|-
| align="right"| 4 || align="right"| 5 || align="right"| 6
|-
| align="right"| 7 || align="right"| 8 || align="right"| 9
|}
Sheet 2:
{| class="wikitable" style="text-align: left;"
|+ <!-- caption -->
|-
| X || Y || Z
|-
| 1.0 || 2.0 || 3.0
|-
| 4.0 || 5.0 || 6.0
|}
Sheet 3:
{| class="wikitable" style="text-align: left;"
|+ <!-- caption -->
|-
| O || P || Q
|-
| 3.0 || 2.0 || 1.0
|-
| 4.0 || 3.0 || 2.0
|}
>>> myfile.close()
>>> book.save_as("myfile.html")
>>> myfile = open("myfile.html")
>>> print(myfile.read()) # doctest: +SKIP
Sheet 1:
<table>
<tr><td style="text-align: right;">1</td><td style="text-align: right;">2</td><td style="text-align: right;">3</td></tr>
<tr><td style="text-align: right;">4</td><td style="text-align: right;">5</td><td style="text-align: right;">6</td></tr>
<tr><td style="text-align: right;">7</td><td style="text-align: right;">8</td><td style="text-align: right;">9</td></tr>
</table>
Sheet 2:
<table>
<tr><td>X </td><td>Y </td><td>Z </td></tr>
<tr><td>1.0</td><td>2.0</td><td>3.0</td></tr>
<tr><td>4.0</td><td>5.0</td><td>6.0</td></tr>
</table>
Sheet 3:
<table>
<tr><td>O </td><td>P </td><td>Q </td></tr>
<tr><td>3.0</td><td>2.0</td><td>1.0</td></tr>
<tr><td>4.0</td><td>3.0</td><td>2.0</td></tr>
</table>
Please note tabulate 0.7.7 gives an extra tbody tag around tr tag.
.. testcode::
:hide:
>>> myfile.close()
>>> import os
>>> os.unlink("myfile.mediawiki")
>>> os.unlink("myfile.html")
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4