3 Python Pandas Tricks for Efficient Data Analysis. Pandas is one of the predominant data analysis tools which is highly appreciated among data scientists. It provides numerous flexible and versatile functions to perform efficient data analysis. In…

Pandas is one of the predominant data analysis tools which is highly appreciated among data scientists. It provides numerous flexible and versatile functions to perform efficient data analysis.

In this article, we will go over 3 pandas tricks that I think will make you a more happy pandas user. It is better to explain these tricks with some examples. Thus, we start by creating a data frame to wok on.

The data frame contains daily sales quantities of 3 different stores. We first create a period of 10 days using the `date_range`

function of pandas.

```
import numpy as np
import pandas as pd
days = pd.date_range("2020-01-01", periods=10, freq="D")
```

The days variable will be used as a column. We also need a sales quantity column which can be generated by the `randint`

function of numpy. Then, we create a data frame with 3 columns for each store.

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