I work with Series and DataFrames on the terminal a lot. The default __repr__
for a Series returns a reduced sample, with some head and tail values, but the rest missing.
Is there a builtin way to pretty-print the entire Series / DataFrame? Ideally, it would support proper alignment, perhaps borders between columns, and maybe even color-coding for the different columns.
No need to hack settings. There is a simple way:
print(df.to_string())
Try this
pd.set_option('display.height',1000)
pd.set_option('display.max_rows',500)
pd.set_option('display.max_columns',500)
pd.set_option('display.width',1000)
pd.options.display
This answer is a variation of the prior answer by lucidyan. It makes the code more readable by avoiding the use of set_option
.
After importing pandas, as an alternative to using the context manager, set such options for displaying large dataframes:
def set_pandas_display_options() -> None:
"""Set pandas display options."""
# Ref: https://stackoverflow.com/a/52432757/
display = pd.options.display
display.max_columns = 1000
display.max_rows = 1000
display.max_colwidth = 199
display.width = None
# display.precision = 2 # set as needed
set_pandas_display_options()
After this, you can use either display(df)
or just df
if using a notebook, otherwise print(df)
.
to_string
Pandas 0.25.3 does have DataFrame.to_string
and Series.to_string
methods which accept formatting options.
to_markdown
If what you need is markdown output, Pandas 1.0.0 has DataFrame.to_markdown
and Series.to_markdown
methods.
to_html
If what you need is HTML output, Pandas 0.25.3 does have a DataFrame.to_html
method but not a Series.to_html
. Note that a Series
can be converted to a DataFrame
.
Sure, if this comes up a lot, make a function like this one. You can even configure it to load every time you start IPython: https://ipython.org/ipython-doc/1/config/overview.html
def print_full(x):
pd.set_option('display.max_rows', len(x))
print(x)
pd.reset_option('display.max_rows')
As for coloring, getting too elaborate with colors sounds counterproductive to me, but I agree something like bootstrap's .table-striped
would be nice. You could always create an issue to suggest this feature.
Use the tabulate package:
pip install tabulate
And consider the following example usage:
import pandas as pd
from io import StringIO
from tabulate import tabulate
c = """Chromosome Start End
chr1 3 6
chr1 5 7
chr1 8 9"""
df = pd.read_table(StringIO(c), sep="\s+", header=0)
print(tabulate(df, headers='keys', tablefmt='psql'))
+----+--------------+---------+-------+
| | Chromosome | Start | End |
|----+--------------+---------+-------|
| 0 | chr1 | 3 | 6 |
| 1 | chr1 | 5 | 7 |
| 2 | chr1 | 8 | 9 |
+----+--------------+---------+-------+
You can achieve this using below method. just pass the total no. of columns present in the DataFrame as arg to
'display.max_columns'
For eg :
df= DataFrame(..)
with pd.option_context('display.max_rows', None, 'display.max_columns', df.shape[1]):
print(df)
Nobody has proposed this simple plain-text solution:
from pprint import pprint
pprint(s.to_dict())
which produces results like the following:
{'% Diabetes': 0.06365372374283895,
'% Obesity': 0.06365372374283895,
'% Bachelors': 0.0,
'% Poverty': 0.09548058561425843,
'% Driving Deaths': 1.1775938892425206,
'% Excessive Drinking': 0.06365372374283895}
Additionally, when using Jupyter notebooks, this is a great solution.
Note: pd.Series()
has no .to_html()
so it must be converted to pd.DataFrame()
from IPython.display import display, HTML
display(HTML(s.to_frame().to_html()))
which produces results like the following:
After importing pandas, as an alternative to using the context manager, set such options for displaying entire dataframes:
pd.set_option('display.max_columns', None) # or 1000
pd.set_option('display.max_rows', None) # or 1000
pd.set_option('display.max_colwidth', -1) # or 199
For full list of useful options, see:
pd.describe_option('display')
If you are using Ipython Notebook (Jupyter). You can use HTML
from IPython.core.display import HTML
display(HTML(df.to_html()))
datascroller was created in part to solve this problem.
pip install datascroller
It loads the dataframe into a terminal view you can "scroll" with your mouse or arrow keys, kind of like an Excel workbook at the terminal that supports querying, highlighting, etc.
import pandas as pd
from datascroller import scroll
# Call `scroll` with a Pandas DataFrame as the sole argument:
my_df = pd.read_csv('<path to your csv>')
scroll(my_df)
Try using display() function. This would automatically use Horizontal and vertical scroll bars and with this you can display different datasets easily instead of using print().
display(dataframe)
display() supports proper alignment also.
However if you want to make the dataset more beautiful you can check pd.option_context()
. It has lot of options to clearly show the dataframe.
Note - I am using Jupyter Notebooks.
Source: Stackoverflow.com