pandas EDA
Big Data? Machine Learning?
You work with your data -
Manipulating it, merging, pivot and more.
But what happened in between? Did you get a lot of nans? Maybe duplicated values?
You constantly need to check your data status,
But you cannot do values_counts, isna and all those stuffs every second...
pandas_eda is an Exploratory Data Analysis tool that will show you status and frequent values for each column!
You will be focused on what you have on the spot.
Demo is the best way to understand:
install:
pip install pandas_eda
usage:
import pandas as pd
import pandas_eda
from time import sleep
# dummy data
df = pd._testing.makeMixedDataFrame()
# or load your data with pd.read_excel('whatever.xlsx')
# show original data. will pop up a web application
df.eda() # can use this at debug mode too!
# that's it. but you can do more...
# manipulation #1
df.A += 10
process = df.eda(title='take 2') # yes, you can open multiple EDA windows!
# process.kill()
# manipulation #2
df.loc[df.B==1, 'A'] -= 30
df.eda()
# no need at jupyter or debug mode...
# ending the script will end the eda too, so delaying the exit.
sleep(600)
headless mode
import pandas as pd
import pandas_eda
# disabling the wrapping of a long table at the print...
pd.options.display.expand_frame_repr = False
pd.options.display.max_columns = 0
pd.options.display.min_rows = 20
df = pandas_eda._testing.generate_fake_table(samples=1_000)
eda = df.eda(cli_mode=True)
print('\n\n *** column statistics *** ')
print(eda.get_columns_statistics())
print('\n\n *** frequent values *** ')
print(eda.get_frequent_values())
testing with
python -m pandas_eda --test
note:
If you're running on remote machine, the eda will be opened on the remote...
alternatives:
After starting this tool I've found 2 cool alternatives:
1 maintainer
Release files for pandas-eda 1.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pandas_eda-1.2.0.tar.gz | 11.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pandas_eda-1.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 21.7 kB
Release files / pandas_eda-1.2.0.tar.gz
| Download URL | pandas_eda-1.2.0.tar.gz |
|---|---|
| Size | 11.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
9873d298f096bd26a3c3d8061b455a837c386d0ed45f94e020722b9ccfa795af
|
|
BLAKE2b-256 checksum How to use checksums |
480140388790fe58d05c2cecea374aab87d1561b260507315041ab6771589c53
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.9.16
|
Release files / pandas_eda-1.2.0-py3-none-any.whl
| Download URL | pandas_eda-1.2.0-py3-none-any.whl |
|---|---|
| Size | 10.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
01ba2cd9b70366577bc7a6c962889964f7931d21d133bd372ac6ea65347c25af
|
|
BLAKE2b-256 checksum How to use checksums |
763e8ac168e242049703423f694fe975e0eea0c41e651b602f266e4ed04a88c1
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.9.16
|
