pandas.tar.gz

Data Wrangling

Data wrangling is cleaning, transforming, and organizing data for further analysis. In this course, you will learn how to use Python to effectively wrangle and prepare data for use in data science and machine learning projects.

Throughout the course, you will learn about the common challenges that arise when working with data and how to overcome them. You will use Python and several libraries commonly used in data wrangling, including NumPy and pandas. Then, you will learn how to use pandas to clean, transform, and aggregate data. Moreover, you will also use scikit-learn, a library for machine learning, to identify outliers in our data.

By the end of the course, you will be able to use Python to effectively wrangle and prepare data for use in data science and machine learning projects. With these tools at your disposal, you can efficiently apply machine learning models and get realistic predictions after applying various wrangling techniques to the dataset.

Data Wrangling With Python

What function should we use to read the `goals.csv` file? 

What function should we use to read the <code>goals.csv</code> file?

We should use `read_excel()` instead of `read_csv()`.

We should import the pandas library in the last line.

What's wrong with the following code that reads an Excel file from a URL?

```
import pandas as pd
people_df = pd.read_csv("http://bit.ly/peopledataset")
print(people_df.head())
```

What’s wrong with the following code that reads an Excel file from a URL?
<pre><code>import pandas as pd
people_df = pd.read_csv(&quot;http://bit.ly/peopledataset&quot;)
print(people_df.head())
</code></pre>

The first five records of `people.xlsx` will be displayed.

The last five records of the dataset will be displayed.

A sample of five records will be displayed.

What will be the output of the following code?

```
import pandas as pd
people_df = pd.read_csv("people.xlsx")
print(people_df.head())
```

What will be the output of the following code?
<pre><code>import pandas as pd
people_df = pd.read_csv(&quot;people.xlsx&quot;)
print(people_df.head())
</code></pre>

What function should we use to read the `medals.json` file? 

What function should we use to read the <code>medals.json</code> file?

What `read_excel()` parameter specifies the worksheet to read data from?

What <code>read_excel()</code> parameter specifies the worksheet to read data from?

Test yourself on the knowledge you learned in the “Reading Data” chapter.

About This Course

Introduction to Data Wrangling

Reading Data

Standardization

Syntax Errors and Irrelevant Data

Duplicate and Missing Data

Filtering and Sorting

Splitting, Combining, and Merging

Handling Outliers

Exporting Data

Humanitarian Aid Project

Conclusion

Quiz Yourself: Reading Data