Analyzing a data structure helps us gather information about the data like how it is stored, what are the different attributes and their properties. Data Analysis can be performed using different python libraries like pandas, etc.
DTale is a Flask and React-based powerful tool which is used to analyze and visualize pandas data structure seamlessly. It supports different objects like Data Frame, Series, etc. It works beautifully on both the Jupyter notebook and the command-line interface.
DTale is a Graphical Interface where we can select the data we want to analyze and how to analyze using different graphs and plots.
In this article, we will explore Dtale with all its functionalities.
Implementation of Dtale
Like any other python library, we need to install DTale before using it by pip install dtale.
- Importing required libraries
We will import Dtale before using it, also we will be downloading our dataset from plotly so we also need to import plotly. You can use any dataset you have.
import dtale
Import plotly.express as px
import pandas as pd
- Loading the dataset
For this article, we will be downloading the dataset named ‘tips’ using Plotly. The dataset contains different attributes of restaurant data.
df = px.data.tips()
df.head()
- Loading Dtale
d = dtale.show(df)
#open it in a new window in browser
d.open_browser()
This is the data frame visualized using Dtale. Here we can change the value of any attribute to our desired value. In this image, you can see the highlighted play button.
When we click on this button we see different functions that are displayed in the image below.
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