"""
hhpy.ipython.py
~~~~~~~~~~~~~~~
Contains convenience wrappers for ipython
"""
# ---- imports
# --- standard imports
import pandas as pd
# --- third party imports
from IPython.display import display, HTML
# --- local imports
from hhpy.main import export, assert_list, list_exclude
# ---- functions
# --- export
[docs]@export
def wide_notebook(width: int = 90):
"""
makes the jupyter notebook wider by appending html code to change the width,
based on https://stackoverflow.com/questions/21971449/how-do-i-increase-the-cell-width-of-the-jupyter-
ipython-notebook-in-my-browser
:param: width in percent, default 90 [optional]
:return: None
"""
# noinspection PyTypeChecker
display(HTML('<style>.container { width:{}% !important; }</style>'.format(width)))
[docs]@export
def hide_code():
"""
hides the code and introduces a toggle button
based on https://stackoverflow.com/questions/27934885/how-to-hide-code-from-cells-in-ipython-notebook-visualized
-with-nbviewer
:return: None
"""
# noinspection PyTypeChecker
display(HTML('''
<script>
code_show=true;
function code_toggle() {
if (code_show){
$('div.input').hide();
} else {
$('div.input').show();
}
code_show = !code_show
}
$( document ).ready(code_toggle);
</script>
The raw code for this IPython notebook is by default hidden for easier reading.
To toggle on/off the raw code, click <a href="javascript:code_toggle()">here</a>.
'''))
[docs]@export
def display_full(*args, rows=None, cols=None, **kwargs):
"""
wrapper to display a pandas DataFrame with all rows and columns
:param rows: number of rows to display, defaults to all
:param cols: number of columns to display, defaults to all
:param args: passed to display
:param kwargs: passed to display
:return: None
"""
with pd.option_context('display.max_rows', rows, 'display.max_columns', cols):
display(*args, **kwargs)
[docs]@export
def pd_display(*args, number_format='{:,.2f}', full=True, **kwargs):
"""
wrapper to display a pandas DataFrame with a specified number format
:param args: passed to display
:param number_format: the number format to apply
:param full: whether to use :func:`~display_full` (True) or standard display (False)
:param kwargs: passed to display
:return: None
"""
pd.set_option('display.float_format', number_format.format)
if full:
display_full(*args, **kwargs)
else:
display(*args, **kwargs)
pd.reset_option('display.float_format')
[docs]@export
def display_df(df, int_format=',', float_format=',.2f', exclude=None, full=True, **kwargs):
"""
Wrapper to display a pandas DataFrame with separate options for int / float, also adds an option to exclude columns
:param df: pandas DataFrame to display
:param int_format: format for integer columns
:param float_format: format for float columns
:param exclude: columns to exclude
:param full: whether to show all rows and columns or keep default behaviour
:param kwargs: passed to display
:return: None
"""
if exclude is None:
exclude = []
else:
exclude = assert_list(exclude)
# avoid inplace
df = pd.DataFrame(df).copy()
_cols_int = list_exclude(df.select_dtypes(int).columns, exclude)
_cols_float = list_exclude(df.select_dtypes(float).columns, exclude)
for _col in _cols_int:
df[_col] = df[_col].apply(lambda _: format(_, int_format) if not pd.isna(_) else '<NaN>')
for _col in _cols_float:
df[_col] = df[_col].apply(lambda _: format(_, float_format) if not pd.isna(_) else '<NaN>')
if full:
display_full(df, **kwargs)
else:
display(df, **kwargs)
# --- pandas styles
[docs]@export
def highlight_max(df: pd.DataFrame, color: str = 'xkcd:cyan') -> pd.DataFrame:
"""
highlights the largest value in each column of a pandas DataFrame
:param df: pandas DataFrame
:param color: color used for highlighting
:return: the pandas DataFrame with the style applied to it
"""
def cond_max(s: pd.Series):
return ['background-color: {}'.format(color) if v else '' for v in s == s.max()]
return df.style.apply(cond_max)
[docs]@export
def highlight_min(df: pd.DataFrame, color: str = 'xkcd:light red') -> pd.DataFrame:
"""
highlights the smallest value in each column of a pandas DataFrame
:param df: pandas DataFrame
:param color: color used for highlighting
:return: the pandas DataFrame with the style applied to it
"""
def cond_min(s: pd.Series):
return ['background-color: {}'.format(color) if v else '' for v in s == s.min()]
return df.style.apply(cond_min)
[docs]@export
def highlight_max_min(df: pd.DataFrame, max_color: str = 'xkcd:cyan', min_color: str = 'xkcd:light red'):
"""
highlights the largest and smallest value in each column of a pandas DataFrame
:param df: pandas DataFrame
:param max_color: color used for highlighting largest value
:param min_color: color used for highlighting smallest value
:return: the pandas DataFrame with the style applied to it
"""
def cond_max_min(s):
_out = []
for _i in s:
if _i == s.max():
_out.append('background-color: {}'.format(max_color))
elif _i == s.min():
_out.append('background-color: {}'.format(min_color))
else:
_out.append('')
return _out
return df.style.apply(cond_max_min)