MACHINE LEARNING RECIPES
DATA CLEANING PYTHON
DATA MUNGING
PANDAS CHEATSHEET
ALL TAGS
# How to compute quantiles using Pandas?

This recipe helps you compute quantiles using Pandas

quantile() function return values at the given quantile over requested axis, a numpy percentile.

So this recipe is a short example on How to compute quantiles in pandas. Let's get started.

```
import pandas as pd
```

Let's pause and look at these imports. Pandas is generally used for performing mathematical operation and preferably over arrays.

```
df = pd.DataFrame({"A":[0, 1, 2, 3, 5, 9],
"B":[11, 5, 8, 6, 7, 8],
"C":[2, 5, 10, 11, 9, 8]})
```

Here we have setup a random dataset with some random values in it.

```
print(df.quantile(.5,axis=0))
print(df.quantile(.25,axis=0))
```

Here we are applied quantile() to find out the quantiles. 0.5 signify median and 0.25, first quater quantile. Similarily we can find any values quantiles.

Once we run the above code snippet, we will see:

Scroll down to the ipython file to look at the results.

We can see the how quantiles being calculated for each series at our specified value.

In this OpenCV project, you will learn computer vision basics and the fundamentals of OpenCV library using Python.

MLOps on GCP - Solved end-to-end MLOps Project to deploy a Mask RCNN Model for Image Segmentation as a Web Application using uWSGI Flask, Docker, and TensorFlow.

In this machine learning project you will work on creating a robust prediction model of Rossmann's daily sales using store, promotion, and competitor data.

In this deep learning project, you will build a convolutional neural network using MNIST dataset for handwritten digit recognition.

In this time series project, you will explore various time series smoothing techniques and build a moving average time series forecasting model in python from scratch.

In this deep learning project, you will learn to implement Unet++ models for medical image segmentation to detect and classify colorectal polyps.

In this OpenCV project, you will learn to implement advanced computer vision concepts and algorithms in OpenCV library using Python.

In this data science project in R, we are going to talk about subjective segmentation which is a clustering technique to find out product bundles in sales data.

Build a time series ARIMA model in Python to forecast the use of arrival rate density to support staffing decisions at call centres.

In this project you will use Python to implement various machine learning methods( RNN, LSTM, GRU) for fake news classification.