Articles · Jul 2020
Data Frame
Harness the simplicity of data visualization with Pandas. Learn how to use pd.DataFrame.plot() to instantly display your DataFrame and create diverse chart types, from lines to…
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Articles · points of view · data hacks
What we have learned, written down.
Points of view for leaders, practical data hacks for practitioners, and conversations from our webinars and podcast.
Articles · Jul 2020
Jupyter Notebook
Jupyter Notebook: a data scientist's secret weapon. Uncover how this versatile IDE empowers developers to showcase and elucidate their code effectively. Leverage Markdown support for enhanced…
Read →Articles · Jul 2020
Precision and Recall
Accuracy is not always the best metric for evaluating machine learning models. Dive into precision and recall metrics, designed to tackle false positives and false negatives.…
Read →Articles · Jul 2020
Pandas
Excel to Pandas: Elevate your data work. Pandas, a Python library, offers powerful data manipulation for data scientists.
Read →Articles · Jun 2020
Data Profiling for Business Analytics
Don't compromise on data quality. Learn how data profiling processes like content discovery, relationship discovery, and structure discovery can enhance the accuracy of your business analytics.…
Read →Articles · Jun 2020
Keep Track of Your Data Lineage
Data lineage demystified: Explore the simplicity of tracking data with identifiers like authors, dates, and access history. Learn why data lineage is a vital asset for…
Read →Articles · Jun 2020
Avoid These Time Killers
Don't let your data project run over schedule. Learn how to combat time-wasting challenges such as resource scarcity, data formatting issues, and sifting through massive datasets.…
Read →Articles · Jun 2020
Develop a Rigid Workflow
Clean, reliable data is the foundation of sound analysis. Explore the eight critical steps in a data workflow, from gathering and verifying data integrity to building…
Read →Articles · Jun 2020
Keep an internal inventory of data sources
It may seem like an obvious point, but it is hard to overemphasize the importance of keeping your own inventory of internal data sources. This will…
Read →Articles · May 2020
Think about Design First
Today's Data Hack Tuesday tip may seem obvious, but is too often overlooked. Before analyzing data for any project, it is important to consider the design…
Read →Articles · May 2020
Cleaning Data in Excel
We all know the old saying: data scientists spend 80% of their time cleaning and manipulating data and only 20% of their time actually analyzing it.…
Read →Articles · May 2020
Cross-validation
We have a simple tip for today to help evaluate models and avoid overfit. Start by separating your data into two sets. These will be the…
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