Data analysts don’t regularly need to write algorithms. But when they do, it might be something that can help them in data analysis. This data analyst interview question is such an example because it asks you t
答案: import pandas as pd # Read the CSV file into a pandas DataFrame data = pd.read_csv('data.csv') # Handle missing values data.dropna(inplace=True) # Handle outliers for column in data.columns: data[column] = handle_outliers(data[column]) # Encode categorical variables for column i...
Statistical Methods:Identify outliers based on statistical properties such as mean and standard deviation. For example, values that are more than 3 standard deviations from the mean can be considered outliers.pythonCopy codeimport numpy as np mean = np.mean(data) std_dev = np.std(data) outliers...
It has certain tools for screening QT forms and translations. Cons: The GUI is not simple. The Eric installation procedure is troublesome. The productivity and performance of Eric seems to be decreased with too many plugins. Go through these Top Python OOPS Interview Questions and Answers to cra...
Python Interview Questions Python Developer Salary Features of Python Difference Between Python 2 and 3 Python Frameworks Python Books Python Developer Resume Applications of Python Python Libraries More Python Developer Skills Data science is a broad term that incorporates data analytics, data mining, Art...
Aakriti is a Technical Research Analyst passionate about machine learning. She is skilled in Python, Machine Learning, and SQL. She excels in qualitative analysis, market research, trend identification, and creating SEO-optimized content. Her unique blend of analytical skills and creative thinking dri...
Section 4: Python DataFrame Interview Questions Lecture 7 Python Interview Questions – DataFrame This course discuss some of the tricky coding interview questions, most commonly asked for Data Analyst job interviews. These are also asked for Data Scientist/ data engineer interviews in the preliminary ...
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Python provides several libraries for analysis, such as pandas and NumPy and for data visualisation, such as Matplotlib. These libraries enable Python developers to analyse complex material and create visualisations to aid decision-making.Related: Frequently Asked Questions: What Is A Data Analyst?
AWS, for example, offers tools for big data storage (S3), warehousing (Redshift), and processing (EMR), and knowing these tools will greatly improve a Python developer’s ability to work with big data. Machine Learning / Deep Learning For a Python data analyst, a little knowledge of ...