Pandas
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What is Pandas?
Pandas is a powerful and flexible Python library used for data manipulation and analysis. It provides data structures like DataFrames (tabular data) and Series (one-dimensional arrays), along with tools for reading and writing data from various file formats (CSV, Excel, SQL databases), cleaning, transforming, and analyzing data. It is commonly used in data science, machine learning, and data analysis workflows.
What other technologies are related to Pandas?
Pandas Competitor Technologies
Polars
Polars is a DataFrame library designed for performance, offering an alternative to Pandas for data manipulation.
PySpark
PySpark is a Python API for Apache Spark, used for large-scale data processing and analysis, often in distributed computing environments. It provides dataframe functionality which competes with Pandas for larger datasets.
Spark
Spark's DataFrame API provides similar functionality to Pandas, but is designed for distributed processing of larger datasets.
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Pandas Complementary Technologies
NumPy
NumPy provides the foundation for Pandas DataFrames and Series, enabling efficient numerical operations.
scikit-learn
Pandas is often used to preprocess and prepare data for scikit-learn models.
Matplotlib
Pandas integrates with Matplotlib for basic data visualization.
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Which job functions commonly mention Pandas?
Data Scientist
10.3% of all Data Scientist jobs mention Pandas
View 25.1k
jobs on Sumble
Machine Learning
8.3% of all Machine Learning jobs mention Pandas
View 8.8k
jobs on Sumble
AI Engineer
5.5% of all AI Engineer jobs mention Pandas
View 4.8k
jobs on Sumble
Data Engineer
3.3% of all Data Engineer jobs mention Pandas
View 9.5k
jobs on Sumble
Data, Analytics & Machine Learning
2.7% of all Data, Analytics & Machine Learning jobs mention Pandas
View 48.2k
jobs on Sumble
Which organizations are mentioning Pandas?
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