fill关键字的用法 Replace null values, alias for na.fill(). DataFrame.fillna() and DataFrameNaFunctions.fill() are aliases of each other. Parameters value –
举例如下。 # Replacingnullvalues dataframe.na.fill() dataFrame.fillna() dataFrameNaFunctions.fill() #Returningnewdataframe restricting rowswithnullvaluesdataframe.na.drop() dataFrame.dropna() dataFrameNaFunctions.drop() #Returnnewdataframe replacing one valuewithanother dataframe.na.replace(5,15) dataFram...
sum() print(f"Total non-null values: {total_non_nulls}") 输出: 代码语言:javascript 复制 Total null values: 5 Total non-null values: 10 结论 通过以上方法,你可以在PySpark中计算数据帧中每列的空值和非空值数量,以及整个数据帧的空值和非空值数量。根据你的具体需求,可以选择适合的方法来实现。
fillna(value[, subset]) Replace null values, alias for na.fill(). 空值填充 filter(condition) Filters rows using the given condition. 条件过滤 first() Returns the first row as a Row. 获取第一行 foreach(f) Applies the f function to all Row of this DataFrame. 将f 函数应用于此 DataFrame ...
# Returning new dataframe restricting rows with null valuesdataframe.na.drop() dataFrame.dropna() dataFrameNaFunctions.drop() # Return new dataframe replacing one value with another dataframe.na.replace(5, 15) dataFrame.replace() dataFrameNaFunctions.replace() ...
(4) replace({-1: 14}, 'stature'): 将stature的-1->14,values参数无效,字典里多个需同类型(string与None不能混用) (5) fillna('haha'): 将null->'haha', 非string值跳过 (6) fillna('xx', [columns_name]): 将多列统一替换na->xx (7) fillna({'f1': 24, 'f2': 'hah'}): 多列分别...
spark_df_json.na.drop()# Replacing Missing Values with Mean spark_df_json.na.fill(spark_df_json.select(f.mean(spark_df_json['state'])).collect()[0][0])# Replacing Missing Values with new values spark_df_json.na.replace(old_value, new_vallue) ...
# 计算一列空值数目 df.filter(df['col_name'].isNull()).count() # 计算每列空值数目 for col in df.columns: print(col, "\t", "with null values: ", df.filter(df[col].isNull()).count()) 平均值填充缺失值 from pyspark.sql.functions import when import pyspark.sql.functions as F #...
Replace null values, alias for na.fill(). DataFrame.fillna() and DataFrameNaFunctions.fill() are aliases of each other. 替换空值, 为 na.fill() 的别名。DataFrame.fillna()和DataFrameNaFunctions.fill()是彼此的别名 filter(condition) Filters rows using the given condition ...
# 计算一列空值数目 df.filter(df['col_name'].isNull()).count() # 计算每列空值数目 for col in df.columns: print(col, "\t", "with null values: ", df.filter(df[col].isNull()).count()) 1. 2. 3. 4. 5. 6. 7. (2)删除有缺失值的行 # 1、删除有缺失值的行 df2 = df...