04_SparkBasics_MissingData.ipynb

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   "source": [
    "import findspark\n",
    "findspark.init('/home/raj/spark-2.1.0-bin-hadoop2.7')\n",
    "import pyspark\n",
    "from pyspark.sql import SparkSession\n",
    "spark=SparkSession.builder.appName('miss').getOrCreate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df=spark.read.csv('/home/raj/Documents/Udemy-Spark/Python-and-Spark-for-Big-Data-master/Spark_DataFrames/ContainsNull.csv'\n",
    "                  ,header=True,inferSchema=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----+-----+-----+\n",
      "|  Id| Name|Sales|\n",
      "+----+-----+-----+\n",
      "|emp1| John| null|\n",
      "|emp2| null| null|\n",
      "|emp3| null|345.0|\n",
      "|emp4|Cindy|456.0|\n",
      "+----+-----+-----+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df.show(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----+-----+-----+\n",
      "|  Id| Name|Sales|\n",
      "+----+-----+-----+\n",
      "|emp1| John| null|\n",
      "|emp3| null|345.0|\n",
      "|emp4|Cindy|456.0|\n",
      "+----+-----+-----+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df.na.drop(thresh=2).show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----+-----+-----+\n",
      "|  Id| Name|Sales|\n",
      "+----+-----+-----+\n",
      "|emp1| John| null|\n",
      "|emp2| null| null|\n",
      "|emp3| null|345.0|\n",
      "|emp4|Cindy|456.0|\n",
      "+----+-----+-----+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df.na.drop(how='all').show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----+-----+-----+\n",
      "|  Id| Name|Sales|\n",
      "+----+-----+-----+\n",
      "|emp3| null|345.0|\n",
      "|emp4|Cindy|456.0|\n",
      "+----+-----+-----+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df.na.drop(subset=['Sales']).show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "root\n",
      " |-- Id: string (nullable = true)\n",
      " |-- Name: string (nullable = true)\n",
      " |-- Sales: double (nullable = true)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df.printSchema()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----+-----------+-----+\n",
      "|  Id|       Name|Sales|\n",
      "+----+-----------+-----+\n",
      "|emp1|       John| null|\n",
      "|emp2|Fill values| null|\n",
      "|emp3|Fill values|345.0|\n",
      "|emp4|      Cindy|456.0|\n",
      "+----+-----------+-----+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df.na.fill('Fill values').show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----+-----+-----+\n",
      "|  Id| Name|Sales|\n",
      "+----+-----+-----+\n",
      "|emp1| John|120.0|\n",
      "|emp2| null|120.0|\n",
      "|emp3| null|345.0|\n",
      "|emp4|Cindy|456.0|\n",
      "+----+-----+-----+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df.na.fill(120.00).show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----+------+-----+\n",
      "|  Id|  Name|Sales|\n",
      "+----+------+-----+\n",
      "|emp1|  John| null|\n",
      "|emp2|NoName| null|\n",
      "|emp3|NoName|345.0|\n",
      "|emp4| Cindy|456.0|\n",
      "+----+------+-----+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df.na.fill('NoName',subset=['Name']).show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from pyspark.sql.functions import mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mean_val=df.select(mean(df['Sales'])).collect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "mean_sales=mean_val[0][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----+-----+-----+\n",
      "|  Id| Name|Sales|\n",
      "+----+-----+-----+\n",
      "|emp1| John|400.5|\n",
      "|emp2| null|400.5|\n",
      "|emp3| null|345.0|\n",
      "|emp4|Cindy|456.0|\n",
      "+----+-----+-----+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df.fillna(mean_sales,['Sales']).show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----+-----+-----+\n",
      "|  Id| Name|Sales|\n",
      "+----+-----+-----+\n",
      "|emp1| John|400.5|\n",
      "|emp2| null|400.5|\n",
      "|emp3| null|345.0|\n",
      "|emp4|Cindy|456.0|\n",
      "+----+-----+-----+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df.na.fill(df.select(mean(df['Sales'])).collect()[0][0],['Sales']).show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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