Pandas in 7 Days: Utilize Python to Manipulate Data, Conduct Scientific Computing, Time Series Analysis (eng)
Table of Contents 1. Pandas, the Python library 2. Setting up a Data Analysis Environment 3. Day 1 - Data Structures in Pandas library 4. Day 2 - Working within a DataFrame, Basic Functionalities 5. Day 3 - Working within a DataFrame, Advanced Functionalities 6. Day 4 - Working with two or more DataFrames 7. Day 5 - Working with data sources and real-word datasets 8. Day 6 - Troubleshooting Challenges wit Real Datasets 9. Day 7 - Data Visualization and Reporting 10. Conclusion – Moving Beyond
Pandas in 7 Days: Utilize Python to Manipulate Data, Conduct Scientific Computing, Time Series Analysis (eng)
Table of Contents 1. Pandas, the Python library 2. Setting up a Data Analysis Environment 3. Day 1 - Data Structures in Pandas library 4. Day 2 - Working within a DataFrame, Basic Functionalities 5. Day 3 - Working within a DataFrame, Advanced Functionalities 6. Day 4 - Working with two or more DataFrames 7. Day 5 - Working with data sources and real-word datasets 8. Day 6 - Troubleshooting Challenges wit Real Datasets 9. Day 7 - Data Visualization and Reporting 10. Conclusion – Moving Beyond
BY Python 🐍 Work With Data
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Pinterest (PINS) closed at $71.75 in the latest trading session, marking a -0.18% move from the prior day. This change lagged the S&P 500's daily gain of 0.1%. Meanwhile, the Dow gained 0.9%, and the Nasdaq, a tech-heavy index, lost 0.59%.
Heading into today, shares of the digital pinboard and shopping tool company had lost 17.41% over the past month, lagging the Computer and Technology sector's loss of 5.38% and the S&P 500's gain of 0.71% in that time.
Investors will be hoping for strength from PINS as it approaches its next earnings release. The company is expected to report EPS of $0.07, up 170% from the prior-year quarter. Our most recent consensus estimate is calling for quarterly revenue of $467.87 million, up 72.05% from the year-ago period.
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