Unlock Python Pandas skills and become a data processing expert!

• Install using pip: pip install <strong class="keylink">pandas</strong>
• Verify installation: import pandas as pd

2. Data structure

• DataFrame: Two-dimensional data structure , rows represent indexes , columns represent column names
• Series: One-dimensional data structure, representing a column of data
• Index: Unique identifier of the data row
• Columns:The name of the data column

3. Data import/export

• read_csv()：Read data from CSV file
• read_excel(): Read data from excel file
• to_csv()：Export data to CSV file
• to_excel()：Export data to Excel file

4. Data cleaning and preprocessing

• fillna()：Fill missing values
• dropna():Delete columns or rows containing missing values
• astype():Forced data type
• unique(): Get the unique value
• groupby():Group data based on one or more columns

5. Data analysis

• describe():Get data statistical information (mean, median, standard deviation)
• corr():Calculate the correlation coefficient between columns
• agg():Aggregation of grouped data (sum, average, maximum)
• plot()：VisualizationData

6. Data conversion

• merge():Merge two DataFrames
• join():Join two DataFrames based on a common key
• concat():Connect multiple DataFrames
• rename(): Rename a column or index

7. Advanced techniques

• lambdas: Used to create anonymous functions
• apply()：Apply the function row by row or column by column
• query():Use Boolean expressions to filter data
• resample():Resample time series data

8. Exercises and Projects

• Kaggle: Participate in data science competitions and gain real-world experience
• Personal Project: Build your own Data AnalysisPipeline
• Online courses: Coursera, edX and other platforms provide advanced Pandas courses

9. Resources

• Pandas official documentation: https://pandas.pydata.org/docs/index.html
• Community Forum: https://stackoverflow.com/questions/tagged/pandas
• books:
  • 《python Data Analysis Manual》
  • 《Pandas Cookbook》

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