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Helper utilities useful with jupyter notebook
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def value_count(x, name=None): | |
''' | |
Helper function that wraps df.value_counts() into a more | |
presentable fashion. | |
Example: | |
======== | |
dat = a|b|c | |
1|2|3 | |
4|5|6 | |
value_counts(dat.a) returns: | |
a|count_a | |
1|1 | |
4|1 | |
value_counts(dat.c) returns: | |
c|count_c | |
3|2 | |
Args: | |
===== | |
x (Pandas Series) data to count | |
name (str, default='count_NAME') name to give to value count | |
column where NAME is `x.name` | |
Yields: | |
======= | |
a dataframe with value_counts() for each unique value in `x` | |
''' | |
name = name if name else 'count_' + str(x.name) | |
counts = pd.DataFrame(pd.Series(x.value_counts(),name=name)) | |
counts.index.name = x.name | |
return counts | |
def load_css(): | |
''' | |
Loads some handy CSS styles into jupyter including the | |
bootstrap styles for <code>, <mark> and .lead | |
Usage: | |
import utils | |
utils.load_css() | |
Make sure this is called as the last command in a cell. | |
''' | |
from IPython.core.display import HTML | |
css = '''<style> | |
code { | |
color: #c7254e !important; | |
background-color: #f9f2f4 !important; | |
font-size: 90% !important; | |
padding: 2px 4px !important; | |
border-radius: 4px !important; | |
} | |
.lead { | |
font-weight: 300 !impotant; | |
line-height: 1.4 !important; | |
font-size: 21px !important; | |
} | |
mark { | |
color: rgb(138, 109, 59) !important; | |
font-weight: bold !important; | |
} | |
</style> | |
''' | |
return HTML(css) |
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