Automated data exploration with pandas profiling
• 2 min read pandas
pip install --upgrade pandas-profiling
Requirement already up-to-date: pandas-profiling in /usr/local/lib/python3.7/dist-packages (3.0.0) Requirement already satisfied, skipping upgrade: joblib in /usr/local/lib/python3.7/dist-packages (from pandas-profiling) (1.0.1) Requirement already satisfied, skipping upgrade: tqdm>=4.48.2 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling) (4.61.0) Requirement already satisfied, skipping upgrade: requests>=2.24.0 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling) (2.25.1) Requirement already satisfied, skipping upgrade: matplotlib>=3.2.0 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling) (3.2.2) Requirement already satisfied, skipping upgrade: jinja2>=2.11.1 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling) (2.11.3) Requirement already satisfied, skipping upgrade: htmlmin>=0.1.12 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling) (0.1.12) Requirement already satisfied, skipping upgrade: visions[type_image_path]==0.7.1 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling) (0.7.1) Requirement already satisfied, skipping upgrade: pandas!=1.0.0,!=1.0.1,!=1.0.2,!=1.1.0,>=0.25.3 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling) (1.1.5) Requirement already satisfied, skipping upgrade: numpy>=1.16.0 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling) (1.19.5) Requirement already satisfied, skipping upgrade: missingno>=0.4.2 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling) (0.4.2) Requirement already satisfied, skipping upgrade: phik>=0.11.1 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling) (0.11.2) Requirement already satisfied, skipping upgrade: tangled-up-in-unicode==0.1.0 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling) (0.1.0) Requirement already satisfied, skipping upgrade: seaborn>=0.10.1 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling) (0.11.1) Requirement already satisfied, skipping upgrade: pydantic>=1.8.1 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling) (1.8.2) Requirement already satisfied, skipping upgrade: scipy>=1.4.1 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling) (1.4.1) Requirement already satisfied, skipping upgrade: PyYAML>=5.0.0 in /usr/local/lib/python3.7/dist-packages (from pandas-profiling) (5.4.1) Requirement already satisfied, skipping upgrade: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests>=2.24.0->pandas-profiling) (1.24.3) Requirement already satisfied, skipping upgrade: chardet<5,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests>=2.24.0->pandas-profiling) (3.0.4) Requirement already satisfied, skipping upgrade: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests>=2.24.0->pandas-profiling) (2.10) Requirement already satisfied, skipping upgrade: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests>=2.24.0->pandas-profiling) (2020.12.5) Requirement already satisfied, skipping upgrade: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib>=3.2.0->pandas-profiling) (2.4.7) Requirement already satisfied, skipping upgrade: cycler>=0.10 in /usr/local/lib/python3.7/dist-packages (from matplotlib>=3.2.0->pandas-profiling) (0.10.0) Requirement already satisfied, skipping upgrade: python-dateutil>=2.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib>=3.2.0->pandas-profiling) (2.8.1) Requirement already satisfied, skipping upgrade: kiwisolver>=1.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib>=3.2.0->pandas-profiling) (1.3.1) Requirement already satisfied, skipping upgrade: MarkupSafe>=0.23 in /usr/local/lib/python3.7/dist-packages (from jinja2>=2.11.1->pandas-profiling) (2.0.1) Requirement already satisfied, skipping upgrade: bottleneck in /usr/local/lib/python3.7/dist-packages (from visions[type_image_path]==0.7.1->pandas-profiling) (1.3.2) Requirement already satisfied, skipping upgrade: networkx>=2.4 in /usr/local/lib/python3.7/dist-packages (from visions[type_image_path]==0.7.1->pandas-profiling) (2.5.1) Requirement already satisfied, skipping upgrade: multimethod==1.4 in /usr/local/lib/python3.7/dist-packages (from visions[type_image_path]==0.7.1->pandas-profiling) (1.4) Requirement already satisfied, skipping upgrade: attrs>=19.3.0 in /usr/local/lib/python3.7/dist-packages (from visions[type_image_path]==0.7.1->pandas-profiling) (21.2.0) Requirement already satisfied, skipping upgrade: imagehash; extra == "type_image_path" in /usr/local/lib/python3.7/dist-packages (from visions[type_image_path]==0.7.1->pandas-profiling) (4.2.0) Requirement already satisfied, skipping upgrade: Pillow; extra == "type_image_path" in /usr/local/lib/python3.7/dist-packages (from visions[type_image_path]==0.7.1->pandas-profiling) (7.1.2) Requirement already satisfied, skipping upgrade: pytz>=2017.2 in /usr/local/lib/python3.7/dist-packages (from pandas!=1.0.0,!=1.0.1,!=1.0.2,!=1.1.0,>=0.25.3->pandas-profiling) (2018.9) Requirement already satisfied, skipping upgrade: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.7/dist-packages (from pydantic>=1.8.1->pandas-profiling) (3.7.4.3) Requirement already satisfied, skipping upgrade: six in /usr/local/lib/python3.7/dist-packages (from cycler>=0.10->matplotlib>=3.2.0->pandas-profiling) (1.15.0) Requirement already satisfied, skipping upgrade: decorator<5,>=4.3 in /usr/local/lib/python3.7/dist-packages (from networkx>=2.4->visions[type_image_path]==0.7.1->pandas-profiling) (4.4.2) Requirement already satisfied, skipping upgrade: PyWavelets in /usr/local/lib/python3.7/dist-packages (from imagehash; extra == "type_image_path"->visions[type_image_path]==0.7.1->pandas-profiling) (1.1.1)
Importing libraries and Titanic dataset
import pandas as pd
from pathlib import Path
from ipywidgets import widgets
from pandas_profiling import ProfileReport
import warnings
warnings.filterwarnings("ignore")
file_name = "https://raw.githubusercontent.com/datasciencedojo/datasets/master/titanic.csv"
df = pd.read_csv(file_name)
profile = ProfileReport(df, title="Titanic Dataset", html={'style': {'full_width': True}}, sort=None)
profile.to_widgets()
profile