Pandas method of reading excel: 1. Read the entire Excel file; 2. Read the specified worksheet; 3. Read multiple worksheets; 4. Specify column names and index columns; 5. Process Missing values and null values, etc. Detailed introduction: 1. To read the entire Excel file, you can use the "read_excel()" method of Pandas to read the entire Excel file. This method requires specifying the file path and worksheet name; 2. Reading the specified worksheet, if you only need Read specific worksheets in Excel files and more.
The operating system for this tutorial: Windows 10 system, DELL G3 computer.
Pandas is a popular Python data analysis library that provides a variety of methods for reading Excel files. The following are common ways to use Pandas to read Excel files:
1. Read the entire Excel file
You can use Pandas's read_excel() method to read the entire Excel file. This method requires specifying the file. Path and worksheet name.
Sample code:
import pandas as pd df = pd.read_excel('file_path.xlsx', sheet_name='Sheet1') # 读取名为'Sheet1'的工作表
2. Read the specified worksheet
If you only need to read a specific worksheet in the Excel file, you can use the read_excel() method Specify the sheet_name parameter.
Sample code:
import pandas as pd df = pd.read_excel('file_path.xlsx', sheet_name='Sheet2') # 读取名为'Sheet2'的工作表
3. Read multiple worksheets
If you want to read multiple worksheets in an Excel file, you can use the read_excel() method Use the sheet_name parameter to specify the names of multiple worksheets to obtain multiple data frame objects.
Sample code:
import pandas as pd dfs = pd.read_excel('file_path.xlsx', sheet_name=['Sheet1', 'Sheet2']) # 获取名为'Sheet1'和'Sheet2'的两个数据框对象
4. Specify column names and index columns
By default, the read_excel() method treats the first row as the column name and the first column as the column name. Treated as an index column. If you want to specify column names and index columns, you can use the header and index_col parameters.
Sample code:
import pandas as pd df = pd.read_excel('file_path.xlsx', header=1, index_col=0) # 将第一行视为列名,将第一列视为索引列
5. Handling missing and empty values
By default, the read_excel() method treats empty cells as NaN values. If you want to specify other values to handle null values, you can use the na_values parameter. Additionally, missing values can be filled using the fillna() method.
Sample code:
import pandas as pd df = pd.read_excel('file_path.xlsx', na_values='N/A') # 将空单元格视为NaN值,但将'N/A'视为一个特殊值 df = df.fillna(0) # 填充缺失值为0
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