要创建新列,请将所需的列名传递给withColumn()函数的第一个参数,第一个参数中的新的列名不能出现在原本的字段名当中,如果出现,会更新该列的值,使用lit()函数可以将常量值加到DataFrame。 df.withColumns("Country",lit("USA")).show() 这个操作如果用SQL的话,就是 select name,dob,gender,salary,"USA" as...
spark=SparkSession.builder.appName("local").enableHiveSupport().getOrCreate() pdf=pd.DataFrame(np.arange(20).reshape(4,5),columns=["a","b","c","d","e"]) df=spark.createDataFrame(pdf) df.agg(fn.count("a").alias("a_count"),fn.countDistinct(df.b),fn.sum("c"),fn.max("d"...
columns Returns the column labels of the DataFrame combine() Compare the values in two DataFrames, and let a function decide which values to keep combine_first() Compare two DataFrames, and if the first DataFrame has a NULL value, it will be filled with the respective value from the second...
print(fill_literal_df) fill_forward_df = df.with_columns( pl.col("col2").fill_null(strategy="forward"), ) print(fill_forward_df) fill_median_df = df.with_columns( pl.col("col2").fill_null(pl.median("col2")), ) print(fill_median_df) fill_interpolation_df = df.with_columns(...
It should be no shock that combining pivot/stack/unstack with GroupBy and the basic Series and DataFrame statistical functions can produce some very expressive and fast data manipulations columns = pd.MultiIndex.from_tuples([('A', 'cat'), ('B', 'dog'), ('B', 'cat'), ('A', 'dog'...
构造 DataFrame：data = df([('along', 30), ('die', 25), ('alpha', 21), ('hack', 34)], columns = ('name', 'age'))输出 name 列以 'a' 开头的所有数据：data[data['name'].str.startswith('a')]data (DataFrame)
DataFrame.query(expr[, inplace])Query the columns of a frame with a boolean expression. 二元运算 方法描述 DataFrame.add(other[, axis, level, fill_value])加法,元素指向 DataFrame.sub(other[, axis, level, fill_value])减法,元素指向 DataFrame.mul(other[, axis, level, fill_value])乘法,元素指...
data.columns.str.endswith("B")array([False,False,False,True])上述代码筛选以B结尾的列，得到相应...
columns_with_word = [col for col in df.columns if 'specific_word' in col] # 创建新的列,并赋予相应的值 new_column = df[columns_with_word].sum(axis=1) # 将新的列添加到原始dataframe中 df = pd.concat([df, new_column.rename('New Column')], axis=1) ...
Steps to Reproduce: run import pandas as pd import numpy as np pd.options.display.max_columns # Create a dataframe with 20 columns df = pd.DataFrame( np.random.randint(0, 100, size=(100, 20)), columns=list("ABCDEFGHIJKLMNOPQRST") ) df.co...