importpandasaspd data={'A':[1,2,3]}df=pd.DataFrame(data)# Creating anewcolumn'D'based on a conditionincolumn'A'df['D']=df['A'].apply(lambda x:'Even'ifx%2==0else'Odd')print(df)Output:AD01Odd12Even23Odd 使用lambda函
df = pd.DataFrame(data) # Creating a new column 'D' based on a condition in column 'A' df['D'] = df['A'].apply(lambda x: 'Even' if x % 2 == 0 else 'Odd') print(df) Output: A D 0 1 Odd 1 2 Even 2 3 Odd 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 1...
df = pd.DataFrame(data) # Creating a new column 'D' based on a condition in column 'A' df['D'] = df['A'].apply(lambda x: 'Even' if x % 2 == 0 else 'Odd') print(df) Output: A D 0 1 Odd 1 2 Even 2 3 Odd 使用lambda函数来检查' a '中的每个元素是偶数还是奇数,并将...
也将矢量化用于条件操作,比如基于列a中的条件创建一个新的列D: importpandasaspddata= {'A': [1, 2, 3]}df = pd.DataFrame(data)#Creatinga new column'D'based on a conditionincolumn'A'df['D'] = df['A'].apply(lambda x: 'Even'ifx %2==0else'Odd') print(df)Output:AD01Odd12Even23...
Columns are the different fields that contain their particular values when we create a DataFrame. We can perform certain operations on both rows & column values. By replacing all the values based on a condition, we mean changing the value of a column when a specific condition is satisfied. ...
基于另一列条件创建新列Pandas[duplicate]可以使用ngroup：
Creating a new column based on if-elif-else condition How to perform cartesian product in pandas? How to find common element or elements in multiple DataFrames? Find the max of two or more columns with pandas? How to select rows in a DataFrame between two values in Python Pandas?
"""making rows out of whole objects instead of parsing them into seperate columns""" # Create the dataset (no data or just the indexes) dataset = pandas.DataFrame(index=names) 追加一列,并且值为svds 代码语言:python 代码运行次数:0 运行 AI代码解释 # Add a column to the dataset where each...
We can create a Pandas pivot table with multiple columns and return reshaped DataFrame. By manipulating given index or column values we can reshape the data based on column values. Use thepandas.pivot_tableto create a spreadsheet-stylepivot table in pandas DataFrame. This function does not suppo...
# We'll use the same dataframe that we used for read_csvframex = df.select_dtypes(include="float64")# Returns only time column 最后,pivot_table() 也是 Pandas 中一个非常有用的函数。如果对 pivot_table() 在 excel 中的使用有所了解,那么就非常容易...