{ "cells": [ { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "%load_ext autoreload\n", "%autoreload 2\n", "import sys\n", "sys.path.append(\"..\")\n", "from optimus import Optimus\n", "\n", "# Create optimus\n", "_load = Optimus(\"ibis\", verbose = True)" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "impala://cloudera:cloudera@35.223.122.210:10000/default\n" ] } ], "source": [ "# Put your db credentials here\n", "db = _load.connect(\n", " driver=\"impala\",\n", " host=\"35.223.122.210\", \n", " database= \"default\", \n", " user= \"cloudera\", \n", " password = \"cloudera\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "df = db.table_to_df(\"prueba\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "_processing = Optimus(\"pandas\", verbose = True)\n", "df = _processing.from_dataframe(df)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Collecting pure-sasl\n", " Downloading pure-sasl-0.6.2.tar.gz (11 kB)\n", "Building wheels for collected packages: pure-sasl\n", " Building wheel for pure-sasl (setup.py): started\n", " Building wheel for pure-sasl (setup.py): finished with status 'done'\n", " Created wheel for pure-sasl: filename=pure_sasl-0.6.2-py3-none-any.whl size=11435 sha256=5aa6d172a618efdeb1b9a62e705812572f668681aed405d6f40a258c76176ab5\n", " Stored in directory: c:\\users\\argenisleon\\appdata\\local\\pip\\cache\\wheels\\60\\6d\\c4\\eeb9f5eae120dce84399f49fc92b447f5b9c2788217aee3209\n", "Successfully built pure-sasl\n", "Installing collected packages: pure-sasl\n", "Successfully installed pure-sasl-0.6.2\n" ] } ], "source": [ "# https://github.com/cloudera/impyla/issues/315\n", "# pip uninstall pure-sasl\n", "#pip uninstall sasl\n", "!pip install pure-sasl" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Without an HDFS connection, certain functionality may be disabled\n" ] } ], "source": [ "import ibis\n", "\n", "hdfs = ibis.impala.hdfs_connect(host='localhost')\n", "con = ibis.impala.connect(user=\"cloudera\", password=\"cloudera\", \n", " host='35.223.122.210', port= 21050, database='default'\n", ")" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['prueba']" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "con.list_tables()" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "table = con.table('prueba', database='default')" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'SELECT *\\nFROM default.`prueba`'" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "table.compile()" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['__bool__',\n", " '__call__',\n", " '__class__',\n", " '__contains__',\n", " '__delattr__',\n", " '__dict__',\n", " '__dir__',\n", " '__doc__',\n", " '__eq__',\n", " '__format__',\n", " '__ge__',\n", " '__getattr__',\n", " '__getattribute__',\n", " '__getitem__',\n", " '__gt__',\n", " '__hash__',\n", " '__init__',\n", " '__init_subclass__',\n", " '__le__',\n", " '__len__',\n", " '__lt__',\n", " '__module__',\n", " '__ne__',\n", " '__new__',\n", " '__nonzero__',\n", " '__reduce__',\n", " '__reduce_ex__',\n", " '__repr__',\n", " '__setattr__',\n", " '__setstate__',\n", " '__sizeof__',\n", " '__str__',\n", " '__subclasshook__',\n", " '__weakref__',\n", " '_alter_table_helper',\n", " '_assert_valid',\n", " '_client',\n", " '_database',\n", " '_ensure_expr',\n", " '_execute',\n", " '_factory',\n", " '_get_type',\n", " '_is_materialized',\n", " '_is_valid',\n", " '_key',\n", " '_match_name',\n", " '_qualified_name',\n", " '_repr',\n", " '_repr_png_',\n", " '_resolve',\n", " '_root_tables',\n", " '_safe_name',\n", " '_type_display',\n", " '_unqualified_name',\n", " 'add_partition',\n", " 'aggregate',\n", " 'alter',\n", " 'alter_partition',\n", " 'anti_join',\n", " 'any_inner_join',\n", " 'any_left_join',\n", " 'asof_join',\n", " 'column_stats',\n", " 'columns',\n", " 'compile',\n", " 'compute_stats',\n", " 'count',\n", " 'cross_join',\n", " 'describe_formatted',\n", " 'difference',\n", " 'distinct',\n", " 'drop',\n", " 'drop_partition',\n", " 'equals',\n", " 'execute',\n", " 'files',\n", " 'filter',\n", " 'get_column',\n", " 'get_columns',\n", " 'group_by',\n", " 'groupby',\n", " 'head',\n", " 'info',\n", " 'inner_join',\n", " 'insert',\n", " 'intersect',\n", " 'invalidate_metadata',\n", " 'is_partitioned',\n", " 'join',\n", " 'left_join',\n", " 'limit',\n", " 'load_data',\n", " 'materialize',\n", " 'metadata',\n", " 'mutate',\n", " 'name',\n", " 'op',\n", " 'outer_join',\n", " 'partition_schema',\n", " 'partitions',\n", " 'pipe',\n", " 'projection',\n", " 'prueba1',\n", " 'refresh',\n", " 'relabel',\n", " 'rename',\n", " 'rowid',\n", " 'schema',\n", " 'select',\n", " 'semi_join',\n", " 'set_column',\n", " 'set_external',\n", " 'sort_by',\n", " 'stats',\n", " 'to_array',\n", " 'truncate',\n", " 'union',\n", " 'verify',\n", " 'view',\n", " 'visualize']" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dir(table)" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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prueba1
0prueba
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" ], "text/plain": [ " prueba1\n", "0 prueba" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "table.execute()\n", "# dir(table)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "ename": "AttributeError", "evalue": "'ImpalaClient' object has no attribute 'tables'", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mcon\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtables\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[1;31mAttributeError\u001b[0m: 'ImpalaClient' object has no attribute 'tables'" ] } ], "source": [ "con.tables()" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['HDFS', 'ImpalaClient', 'ImpalaConnection', 'ImpalaDatabase', 'ImpalaTable', 'WebHDFS', '__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__path__', '__spec__', 'add_operation', 'aggregate_function', 'client', 'com', 'compat', 'compile', 'compiler', 'connect', 'ddl', 'dialect', 'hdfs_connect', 'options', 'scalar_function', 'udf', 'verify', 'wrap_uda', 'wrap_udf']\n" ] }, { "ename": "TypeError", "evalue": "connect() got an unexpected keyword argument 'url'", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mdb\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtables\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[1;32m~\\Documents\\Optimus\\optimus\\engines\\ibis\\io\\jdbc.py\u001b[0m in \u001b[0;36mtables\u001b[1;34m(self, schema, database, limit)\u001b[0m\n\u001b[0;32m 53\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mtables\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mschema\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdatabase\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlimit\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 54\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdir\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mibis\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mimpala\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 55\u001b[1;33m \u001b[0mcon\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mibis\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mimpala\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0muri\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 56\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mcon\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlist_tables\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 57\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;31mTypeError\u001b[0m: connect() got an unexpected keyword argument 'url'" ] } ], "source": [ "db.tables()" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "ename": "StatementError", "evalue": "(thriftpy2.protocol.exc.TProtocolException) No protocol version header\n[SQL: SELECT * FROM prueba LIMIT 0]", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mTProtocolException\u001b[0m Traceback (most recent call last)", "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\sqlalchemy\\engine\\base.py\u001b[0m in \u001b[0;36m_execute_context\u001b[1;34m(self, dialect, constructor, statement, parameters, *args)\u001b[0m\n\u001b[0;32m 1178\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1179\u001b[1;33m \u001b[0mcontext\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mconstructor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdialect\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mconn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1180\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mBaseException\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\sqlalchemy\\engine\\default.py\u001b[0m in \u001b[0;36m_init_statement\u001b[1;34m(cls, dialect, connection, dbapi_connection, statement, parameters)\u001b[0m\n\u001b[0;32m 908\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 909\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcursor\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcreate_cursor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 910\u001b[0m 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\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_dbapi_connection\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcursor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mconfiguration\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcursor_configuration\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 138\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\sqlalchemy\\pool\\base.py\u001b[0m in \u001b[0;36mcursor\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m 964\u001b[0m \"\"\"\n\u001b[1;32m--> 965\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconnection\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcursor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 966\u001b[0m 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\u001b[0merr_if_rpc_not_ok\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mresponse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\impala\\hiveserver2.py\u001b[0m in \u001b[0;36m_execute\u001b[1;34m(self, func_name, request)\u001b[0m\n\u001b[0;32m 1008\u001b[0m \u001b[0mlog\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdebug\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Transport opened'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1009\u001b[0m \u001b[0mfunc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclient\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfunc_name\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1010\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrequest\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1011\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0msocket\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0merror\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1012\u001b[0m log.exception('Failed to open transport (tries_left=%s)',\n", "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\thriftpy2\\thrift.py\u001b[0m in \u001b[0;36m_req\u001b[1;34m(self, _api, *args, **kwargs)\u001b[0m\n\u001b[0;32m 217\u001b[0m \u001b[1;31m# wait result only if non-oneway\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 218\u001b[0m \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mresult_cls\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"oneway\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 219\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_recv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0m_api\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 220\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 221\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_send\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0m_api\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\thriftpy2\\thrift.py\u001b[0m in \u001b[0;36m_recv\u001b[1;34m(self, _api)\u001b[0m\n\u001b[0;32m 229\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 230\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_recv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0m_api\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 231\u001b[1;33m \u001b[0mfname\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmtype\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mrseqid\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_iprot\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_message_begin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 232\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mmtype\u001b[0m \u001b[1;33m==\u001b[0m \u001b[0mTMessageType\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mEXCEPTION\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 233\u001b[0m \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mTApplicationException\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\thriftpy2\\protocol\\binary.py\u001b[0m in \u001b[0;36mread_message_begin\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 371\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mread_message_begin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 372\u001b[0m api, ttype, seqid = read_message_begin(\n\u001b[1;32m--> 373\u001b[1;33m self.trans, strict=self.strict_read)\n\u001b[0m\u001b[0;32m 374\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mapi\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mttype\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mseqid\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 375\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\thriftpy2\\protocol\\binary.py\u001b[0m in \u001b[0;36mread_message_begin\u001b[1;34m(inbuf, strict)\u001b[0m\n\u001b[0;32m 177\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mstrict\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 178\u001b[0m raise TProtocolException(type=TProtocolException.BAD_VERSION,\n\u001b[1;32m--> 179\u001b[1;33m message='No protocol version header')\n\u001b[0m\u001b[0;32m 180\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 181\u001b[0m \u001b[0mname\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0minbuf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msz\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdecode\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'utf-8'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;31mStatementError\u001b[0m: (thriftpy2.protocol.exc.TProtocolException) No protocol version header\n[SQL: SELECT * FROM prueba LIMIT 0]" ] } ], "source": [ "db.table_to_df(\"prueba\").ext.display()" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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INCIDENT_NUMBEROFFENSE_CODEOFFENSE_CODE_GROUPOFFENSE_DESCRIPTIONDISTRICTREPORTING_AREASHOOTINGOCCURRED_ON_DATEYEARMONTHDAY_OF_WEEKHOURUCR_PARTSTREETLatLongLocation
0I18207094500619LarcenyLARCENY ALL OTHERSD148082018-09-02 13:00:0020189Sunday13Part OneLINCOLN ST42.35779134-71.13937053(42.35779134, -71.13937053)
1I18207094301402VandalismVANDALISMC113472018-08-21 00:00:0020188Tuesday0Part TwoHECLA ST42.30682138-71.06030035(42.30682138, -71.06030035)
2I18207094103410TowedTOWED MOTOR VEHICLED41512018-09-03 19:27:0020189Monday19Part ThreeCAZENOVE ST42.34658879-71.07242943(42.34658879, -71.07242943)
3I18207094003114Investigate PropertyINVESTIGATE PROPERTYD42722018-09-03 21:16:0020189Monday21Part ThreeNEWCOMB ST42.33418175-71.07866441(42.33418175, -71.07866441)
4I18207093803114Investigate PropertyINVESTIGATE PROPERTYB34212018-09-03 21:05:0020189Monday21Part ThreeDELHI ST42.27536542-71.09036101(42.27536542, -71.09036101)
5I18207093603820Motor Vehicle Accident ResponseM/V ACCIDENT INVOLVING PEDESTRIAN - INJURYC113982018-09-03 21:09:0020189Monday21Part ThreeTALBOT AVE42.29019621-71.07159012(42.29019621, -71.07159012)
6I18207093300724Auto TheftAUTO THEFTB23302018-09-03 21:25:0020189Monday21Part OneNORMANDY ST42.30607218-71.08273260(42.30607218, -71.08273260)
7I18207093203301Verbal DisputesVERBAL DISPUTEB25842018-09-03 20:39:3720189Monday20Part ThreeLAWN ST42.32701648-71.10555088(42.32701648, -71.10555088)
8I18207093100301RobberyROBBERY - STREETC61772018-09-03 20:48:0020189Monday20Part OneMASSACHUSETTS AVE42.33152148-71.07085307(42.33152148, -71.07085307)
9I18207092903301Verbal DisputesVERBAL DISPUTEC113642018-09-03 20:38:0020189Monday20Part ThreeLESLIE ST42.29514664-71.05860832(42.29514664, -71.05860832)
\n", "
" ], "text/plain": [ " INCIDENT_NUMBER OFFENSE_CODE OFFENSE_CODE_GROUP \\\n", "0 I182070945 00619 Larceny \n", "1 I182070943 01402 Vandalism \n", "2 I182070941 03410 Towed \n", "3 I182070940 03114 Investigate Property \n", "4 I182070938 03114 Investigate Property \n", "5 I182070936 03820 Motor Vehicle Accident Response \n", "6 I182070933 00724 Auto Theft \n", "7 I182070932 03301 Verbal Disputes \n", "8 I182070931 00301 Robbery \n", "9 I182070929 03301 Verbal Disputes \n", "\n", " OFFENSE_DESCRIPTION DISTRICT REPORTING_AREA \\\n", "0 LARCENY ALL OTHERS D14 808 \n", "1 VANDALISM C11 347 \n", "2 TOWED MOTOR VEHICLE D4 151 \n", "3 INVESTIGATE PROPERTY D4 272 \n", "4 INVESTIGATE PROPERTY B3 421 \n", "5 M/V ACCIDENT INVOLVING PEDESTRIAN - INJURY C11 398 \n", "6 AUTO THEFT B2 330 \n", "7 VERBAL DISPUTE B2 584 \n", "8 ROBBERY - STREET C6 177 \n", "9 VERBAL DISPUTE C11 364 \n", "\n", " SHOOTING OCCURRED_ON_DATE YEAR MONTH DAY_OF_WEEK HOUR UCR_PART \\\n", "0 2018-09-02 13:00:00 2018 9 Sunday 13 Part One \n", "1 2018-08-21 00:00:00 2018 8 Tuesday 0 Part Two \n", "2 2018-09-03 19:27:00 2018 9 Monday 19 Part Three \n", "3 2018-09-03 21:16:00 2018 9 Monday 21 Part Three \n", "4 2018-09-03 21:05:00 2018 9 Monday 21 Part Three \n", "5 2018-09-03 21:09:00 2018 9 Monday 21 Part Three \n", "6 2018-09-03 21:25:00 2018 9 Monday 21 Part One \n", "7 2018-09-03 20:39:37 2018 9 Monday 20 Part Three \n", "8 2018-09-03 20:48:00 2018 9 Monday 20 Part One \n", "9 2018-09-03 20:38:00 2018 9 Monday 20 Part Three \n", "\n", " STREET Lat Long Location \n", "0 LINCOLN ST 42.35779134 -71.13937053 (42.35779134, -71.13937053) \n", "1 HECLA ST 42.30682138 -71.06030035 (42.30682138, -71.06030035) \n", "2 CAZENOVE ST 42.34658879 -71.07242943 (42.34658879, -71.07242943) \n", "3 NEWCOMB ST 42.33418175 -71.07866441 (42.33418175, -71.07866441) \n", "4 DELHI ST 42.27536542 -71.09036101 (42.27536542, -71.09036101) \n", "5 TALBOT AVE 42.29019621 -71.07159012 (42.29019621, -71.07159012) \n", "6 NORMANDY ST 42.30607218 -71.08273260 (42.30607218, -71.08273260) \n", "7 LAWN ST 42.32701648 -71.10555088 (42.32701648, -71.10555088) \n", "8 MASSACHUSETTS AVE 42.33152148 -71.07085307 (42.33152148, -71.07085307) \n", "9 LESLIE ST 42.29514664 -71.05860832 (42.29514664, -71.05860832) " ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head()" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "df1 = df.cols.lower(\"INCIDENT_NUMBER\")" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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INCIDENT_NUMBEROFFENSE_CODEOFFENSE_CODE_GROUPOFFENSE_DESCRIPTIONDISTRICTREPORTING_AREASHOOTINGOCCURRED_ON_DATEYEARMONTHDAY_OF_WEEKHOURUCR_PARTSTREETLatLongLocation
0I18207094500619LarcenyLARCENY ALL OTHERSD148082018-09-02 13:00:0020189Sunday13Part OneLINCOLN ST42.35779134-71.13937053(42.35779134, -71.13937053)
1I18207094301402VandalismVANDALISMC113472018-08-21 00:00:0020188Tuesday0Part TwoHECLA ST42.30682138-71.06030035(42.30682138, -71.06030035)
2I18207094103410TowedTOWED MOTOR VEHICLED41512018-09-03 19:27:0020189Monday19Part ThreeCAZENOVE ST42.34658879-71.07242943(42.34658879, -71.07242943)
3I18207094003114Investigate PropertyINVESTIGATE PROPERTYD42722018-09-03 21:16:0020189Monday21Part ThreeNEWCOMB ST42.33418175-71.07866441(42.33418175, -71.07866441)
4I18207093803114Investigate PropertyINVESTIGATE PROPERTYB34212018-09-03 21:05:0020189Monday21Part ThreeDELHI ST42.27536542-71.09036101(42.27536542, -71.09036101)
......................................................
319068I050310906-0003125Warrant ArrestsWARRANT ARRESTD42852016-06-05 17:25:0020166Sunday17Part ThreeCOVENTRY ST42.33695098-71.08574813(42.33695098, -71.08574813)
319069I030217815-0800111HomicideMURDER, NON-NEGLIGIENT MANSLAUGHTERE185202015-07-09 13:38:0020157Thursday13Part OneRIVER ST42.25592648-71.12317207(42.25592648, -71.12317207)
319070I030217815-0803125Warrant ArrestsWARRANT ARRESTE185202015-07-09 13:38:0020157Thursday13Part ThreeRIVER ST42.25592648-71.12317207(42.25592648, -71.12317207)
319071I010370257-0003125Warrant ArrestsWARRANT ARRESTE135692016-05-31 19:35:0020165Tuesday19Part ThreeNEW WASHINGTON ST42.30233307-71.11156487(42.30233307, -71.11156487)
31907214205255003125Warrant ArrestsWARRANT ARRESTD49032015-06-22 00:12:0020156Monday0Part ThreeWASHINGTON ST42.33383935-71.08029038(42.33383935, -71.08029038)
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319073 rows × 17 columns

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" ], "text/plain": [ " INCIDENT_NUMBER OFFENSE_CODE OFFENSE_CODE_GROUP \\\n", "0 I182070945 00619 Larceny \n", "1 I182070943 01402 Vandalism \n", "2 I182070941 03410 Towed \n", "3 I182070940 03114 Investigate Property \n", "4 I182070938 03114 Investigate Property \n", "... ... ... ... \n", "319068 I050310906-00 03125 Warrant Arrests \n", "319069 I030217815-08 00111 Homicide \n", "319070 I030217815-08 03125 Warrant Arrests \n", "319071 I010370257-00 03125 Warrant Arrests \n", "319072 142052550 03125 Warrant Arrests \n", "\n", " OFFENSE_DESCRIPTION DISTRICT REPORTING_AREA SHOOTING \\\n", "0 LARCENY ALL OTHERS D14 808 \n", "1 VANDALISM C11 347 \n", "2 TOWED MOTOR VEHICLE D4 151 \n", "3 INVESTIGATE PROPERTY D4 272 \n", "4 INVESTIGATE PROPERTY B3 421 \n", "... ... ... ... ... \n", "319068 WARRANT ARREST D4 285 \n", "319069 MURDER, NON-NEGLIGIENT MANSLAUGHTER E18 520 \n", "319070 WARRANT ARREST E18 520 \n", "319071 WARRANT ARREST E13 569 \n", "319072 WARRANT ARREST D4 903 \n", "\n", " OCCURRED_ON_DATE YEAR MONTH DAY_OF_WEEK HOUR UCR_PART \\\n", "0 2018-09-02 13:00:00 2018 9 Sunday 13 Part One \n", "1 2018-08-21 00:00:00 2018 8 Tuesday 0 Part Two \n", "2 2018-09-03 19:27:00 2018 9 Monday 19 Part Three \n", "3 2018-09-03 21:16:00 2018 9 Monday 21 Part Three \n", "4 2018-09-03 21:05:00 2018 9 Monday 21 Part Three \n", "... ... ... ... ... ... ... \n", "319068 2016-06-05 17:25:00 2016 6 Sunday 17 Part Three \n", "319069 2015-07-09 13:38:00 2015 7 Thursday 13 Part One \n", "319070 2015-07-09 13:38:00 2015 7 Thursday 13 Part Three \n", "319071 2016-05-31 19:35:00 2016 5 Tuesday 19 Part Three \n", "319072 2015-06-22 00:12:00 2015 6 Monday 0 Part Three \n", "\n", " STREET Lat Long \\\n", "0 LINCOLN ST 42.35779134 -71.13937053 \n", "1 HECLA ST 42.30682138 -71.06030035 \n", "2 CAZENOVE ST 42.34658879 -71.07242943 \n", "3 NEWCOMB ST 42.33418175 -71.07866441 \n", "4 DELHI ST 42.27536542 -71.09036101 \n", "... ... ... ... \n", "319068 COVENTRY ST 42.33695098 -71.08574813 \n", "319069 RIVER ST 42.25592648 -71.12317207 \n", "319070 RIVER ST 42.25592648 -71.12317207 \n", "319071 NEW WASHINGTON ST 42.30233307 -71.11156487 \n", "319072 WASHINGTON ST 42.33383935 -71.08029038 \n", "\n", " Location \n", "0 (42.35779134, -71.13937053) \n", "1 (42.30682138, -71.06030035) \n", "2 (42.34658879, -71.07242943) \n", "3 (42.33418175, -71.07866441) \n", "4 (42.27536542, -71.09036101) \n", "... ... \n", "319068 (42.33695098, -71.08574813) \n", "319069 (42.25592648, -71.12317207) \n", "319070 (42.25592648, -71.12317207) \n", "319071 (42.30233307, -71.11156487) \n", "319072 (42.33383935, -71.08029038) \n", "\n", "[319073 rows x 17 columns]" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.to_pandas()" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "
Viewing 10 of 319073 rows / 17 columns
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N/A partition(s)
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INCIDENT_NUMBER
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1 (object)
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OFFENSE_CODE
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2 (object)
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OFFENSE_CODE_GROUP
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3 (object)
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OFFENSE_DESCRIPTION
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4 (object)
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DISTRICT
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5 (object)
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REPORTING_AREA
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6 (object)
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SHOOTING
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7 (object)
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OCCURRED_ON_DATE
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8 (object)
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YEAR
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9 (object)
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MONTH
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10 (object)
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DAY_OF_WEEK
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11 (object)
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HOUR
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12 (object)
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UCR_PART
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13 (object)
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STREET
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14 (object)
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\n", " 		\n", "
Lat
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15 (object)
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Long
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16 (object)
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\n", " 		\n", "
Location
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17 (object)
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\n", "
\n", " \n", " I182070945\n", " \n", "
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\n", " 		\n", "
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\n", " 		\n", "
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\n", " \n", " -71.08273260\n", " \n", "
\n", " 		\n", "
\n", " \n", " (42.30607218,⋅-71.08273260)\n", " \n", "
\n", "
\n", "
\n", " \n", " I182070932\n", " \n", "
\n", " 		\n", "
\n", " \n", " 03301\n", " \n", "
\n", " 		\n", "
\n", " \n", " Verbal⋅Disputes\n", " \n", "
\n", " 		\n", "
\n", " \n", " verbal⋅dispute\n", " \n", "
\n", " 		\n", "
\n", " \n", " B2\n", " \n", "
\n", " 		\n", "
\n", " \n", " 584\n", " \n", "
\n", " 		\n", "
\n", " \n", " \n", " \n", "
\n", " 		\n", "
\n", " \n", " 2018-09-03⋅20:39:37\n", " \n", "
\n", " 		\n", "
\n", " \n", " 2018\n", " \n", "
\n", " 		\n", "
\n", " \n", " 9\n", " \n", "
\n", " 		\n", "
\n", " \n", " Monday\n", " \n", "
\n", " 		\n", "
\n", " \n", " 20\n", " \n", "
\n", " 		\n", "
\n", " \n", " Part⋅Three\n", " \n", "
\n", " 		\n", "
\n", " \n", " LAWN⋅ST\n", " \n", "
\n", " 		\n", "
\n", " \n", " 42.32701648\n", " \n", "
\n", " 		\n", "
\n", " \n", " -71.10555088\n", " \n", "
\n", " 		\n", "
\n", " \n", " (42.32701648,⋅-71.10555088)\n", " \n", "
\n", "
\n", "
\n", " \n", " I182070931\n", " \n", "
\n", " 		\n", "
\n", " \n", " 00301\n", " \n", "
\n", " 		\n", "
\n", " \n", " Robbery\n", " \n", "
\n", " 		\n", "
\n", " \n", " robbery⋅-⋅street\n", " \n", "
\n", " 		\n", "
\n", " \n", " C6\n", " \n", "
\n", " 		\n", "
\n", " \n", " 177\n", " \n", "
\n", " 		\n", "
\n", " \n", " \n", " \n", "
\n", " 		\n", "
\n", " \n", " 2018-09-03⋅20:48:00\n", " \n", "
\n", " 		\n", "
\n", " \n", " 2018\n", " \n", "
\n", " 		\n", "
\n", " \n", " 9\n", " \n", "
\n", " 		\n", "
\n", " \n", " Monday\n", " \n", "
\n", " 		\n", "
\n", " \n", " 20\n", " \n", "
\n", " 		\n", "
\n", " \n", " Part⋅One\n", " \n", "
\n", " 		\n", "
\n", " \n", " MASSACHUSETTS⋅AVE\n", " \n", "
\n", " 		\n", "
\n", " \n", " 42.33152148\n", " \n", "
\n", " 		\n", "
\n", " \n", " -71.07085307\n", " \n", "
\n", " 		\n", "
\n", " \n", " (42.33152148,⋅-71.07085307)\n", " \n", "
\n", "
\n", "\n", "
Viewing 10 of 319073 rows / 17 columns
\n", "
N/A partition(s) <class 'optimus.engines.pandas.dataframe.PandasDataFrame'>
\n", "\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.to_optimus_pandas().cols.lower(\"OFFENSE_DESCRIPTION\")" ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'profile': {'columns': {'INCIDENT_NUMBER': {'profiler_dtype': {'dtype': 'string'},\n", " 'stats': {'match': 319073,\n", " 'missing': 0,\n", " 'mismatch': 0,\n", " 'profiler_dtype': {'dtype': 'string'},\n", " 'frequency': [{'value': 'I162030584', 'count': 13},\n", " {'value': 'I152080623', 'count': 11},\n", " {'value': 'I172013170', 'count': 10},\n", " {'value': 'I182065208', 'count': 10},\n", " {'value': 'I172096394', 'count': 10},\n", " {'value': 'I162071327', 'count': 9},\n", " {'value': 'I162001871', 'count': 9},\n", " {'value': 'I172056883', 'count': 9},\n", " {'value': 'I172054429', 'count': 9},\n", " {'value': 'I162098170', 'count': 9},\n", " {'value': 'I172022524', 'count': 9},\n", " {'value': 'I152076465', 'count': 8},\n", " {'value': 'I172053616', 'count': 8},\n", " {'value': 'I152105431', 'count': 8},\n", " {'value': 'I162082917', 'count': 8},\n", " {'value': 'I162064331', 'count': 8},\n", " {'value': 'I162056703', 'count': 8},\n", " {'value': 'I130041200-00', 'count': 8},\n", " {'value': 'I162087224', 'count': 8},\n", " {'value': 'I162022140', 'count': 8},\n", " {'value': 'I172069723', 'count': 8},\n", " {'value': 'I162090278', 'count': 8},\n", " {'value': 'I162074826', 'count': 8},\n", " {'value': 'I162078338', 'count': 8},\n", " {'value': 'I152101399', 'count': 7},\n", " {'value': 'I152095733', 'count': 7},\n", " {'value': 'I162054378', 'count': 7},\n", " {'value': 'I152067057', 'count': 7},\n", " {'value': 'I152096998', 'count': 7},\n", " {'value': 'I172018004', 'count': 7},\n", " {'value': 'I162083089', 'count': 7},\n", " {'value': 'I162045680', 'count': 7},\n", " {'value': 'I152071480', 'count': 7}],\n", " 'count_uniques': 282517},\n", " 'dtype': 'object'}},\n", " 'name': None,\n", " 'file_name': None,\n", " 'summary': {'cols_count': 17,\n", " 'rows_count': 319073,\n", " 'dtypes_list': ['object'],\n", " 'total_count_dtypes': 1,\n", " 'missing_count': 0,\n", " 'p_missing': 0.0}},\n", " 'transformations': {'actions': []}}" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.meta" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "
Viewing 10 of 319073 rows / 1 columns
\n", "
1 partition(s)
\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
\n", "
INCIDENT_NUMBER
\n", "
1 (object)
\n", "
\n", " \n", " not nullable\n", " \n", "
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\n", "
\n", " \n", " I182016471\n", " \n", "
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\n", " \n", " I182062395\n", " \n", "
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\n", "
\n", " \n", " I162052877\n", " \n", "
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\n", "
\n", " \n", " I162067216\n", " \n", "
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\n", "
\n", " \n", " I172079919\n", " \n", "
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\n", "
\n", " \n", " I162027167\n", " \n", "
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\n", "
\n", " \n", " I162039177\n", " \n", "
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\n", "
\n", " \n", " I172093225\n", " \n", "
\n", "
\n", "
\n", " \n", " I162030885\n", " \n", "
\n", "
\n", "
\n", " \n", " I162028326\n", " \n", "
\n", "
\n", "\n", "
Viewing 10 of 319073 rows / 1 columns
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1 partition(s) <class 'optimus.engines.dask.dataframe.DaskDataFrame'>
\n", "\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df[0]" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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INCIDENT_NUMBEROFFENSE_CODEOFFENSE_CODE_GROUPOFFENSE_DESCRIPTIONDISTRICTREPORTING_AREASHOOTINGOCCURRED_ON_DATEYEARMONTHDAY_OF_WEEKHOURUCR_PARTSTREETLatLongLocation
0larceny00619LarcenyLARCENY ALL OTHERSD148082018-09-02 13:00:0020189Sunday13Part OneLINCOLN ST42.35779134-71.13937053(42.35779134, -71.13937053)
1I18207094301402VandalismVANDALISMC113472018-08-21 00:00:0020188Tuesday0Part TwoHECLA ST42.30682138-71.06030035(42.30682138, -71.06030035)
2I18207094103410TowedTOWED MOTOR VEHICLED41512018-09-03 19:27:0020189Monday19Part ThreeCAZENOVE ST42.34658879-71.07242943(42.34658879, -71.07242943)
3I18207094003114Investigate PropertyINVESTIGATE PROPERTYD42722018-09-03 21:16:0020189Monday21Part ThreeNEWCOMB ST42.33418175-71.07866441(42.33418175, -71.07866441)
4I18207093803114Investigate PropertyINVESTIGATE PROPERTYB34212018-09-03 21:05:0020189Monday21Part ThreeDELHI ST42.27536542-71.09036101(42.27536542, -71.09036101)
......................................................
319068I050310906-0003125Warrant ArrestsWARRANT ARRESTD42852016-06-05 17:25:0020166Sunday17Part ThreeCOVENTRY ST42.33695098-71.08574813(42.33695098, -71.08574813)
319069I030217815-0800111HomicideMURDER, NON-NEGLIGIENT MANSLAUGHTERE185202015-07-09 13:38:0020157Thursday13Part OneRIVER ST42.25592648-71.12317207(42.25592648, -71.12317207)
319070I030217815-0803125Warrant ArrestsWARRANT ARRESTE185202015-07-09 13:38:0020157Thursday13Part ThreeRIVER ST42.25592648-71.12317207(42.25592648, -71.12317207)
319071I010370257-0003125Warrant ArrestsWARRANT ARRESTE135692016-05-31 19:35:0020165Tuesday19Part ThreeNEW WASHINGTON ST42.30233307-71.11156487(42.30233307, -71.11156487)
31907214205255003125Warrant ArrestsWARRANT ARRESTD49032015-06-22 00:12:0020156Monday0Part ThreeWASHINGTON ST42.33383935-71.08029038(42.33383935, -71.08029038)
\n", "

319073 rows × 17 columns

\n", "
" ], "text/plain": [ " INCIDENT_NUMBER OFFENSE_CODE OFFENSE_CODE_GROUP \\\n", "0 larceny 00619 Larceny \n", "1 I182070943 01402 Vandalism \n", "2 I182070941 03410 Towed \n", "3 I182070940 03114 Investigate Property \n", "4 I182070938 03114 Investigate Property \n", "... ... ... ... \n", "319068 I050310906-00 03125 Warrant Arrests \n", "319069 I030217815-08 00111 Homicide \n", "319070 I030217815-08 03125 Warrant Arrests \n", "319071 I010370257-00 03125 Warrant Arrests \n", "319072 142052550 03125 Warrant Arrests \n", "\n", " OFFENSE_DESCRIPTION DISTRICT REPORTING_AREA SHOOTING \\\n", "0 LARCENY ALL OTHERS D14 808 \n", "1 VANDALISM C11 347 \n", "2 TOWED MOTOR VEHICLE D4 151 \n", "3 INVESTIGATE PROPERTY D4 272 \n", "4 INVESTIGATE PROPERTY B3 421 \n", "... ... ... ... ... \n", "319068 WARRANT ARREST D4 285 \n", "319069 MURDER, NON-NEGLIGIENT MANSLAUGHTER E18 520 \n", "319070 WARRANT ARREST E18 520 \n", "319071 WARRANT ARREST E13 569 \n", "319072 WARRANT ARREST D4 903 \n", "\n", " OCCURRED_ON_DATE YEAR MONTH DAY_OF_WEEK HOUR UCR_PART \\\n", "0 2018-09-02 13:00:00 2018 9 Sunday 13 Part One \n", "1 2018-08-21 00:00:00 2018 8 Tuesday 0 Part Two \n", "2 2018-09-03 19:27:00 2018 9 Monday 19 Part Three \n", "3 2018-09-03 21:16:00 2018 9 Monday 21 Part Three \n", "4 2018-09-03 21:05:00 2018 9 Monday 21 Part Three \n", "... ... ... ... ... ... ... \n", "319068 2016-06-05 17:25:00 2016 6 Sunday 17 Part Three \n", "319069 2015-07-09 13:38:00 2015 7 Thursday 13 Part One \n", "319070 2015-07-09 13:38:00 2015 7 Thursday 13 Part Three \n", "319071 2016-05-31 19:35:00 2016 5 Tuesday 19 Part Three \n", "319072 2015-06-22 00:12:00 2015 6 Monday 0 Part Three \n", "\n", " STREET Lat Long \\\n", "0 LINCOLN ST 42.35779134 -71.13937053 \n", "1 HECLA ST 42.30682138 -71.06030035 \n", "2 CAZENOVE ST 42.34658879 -71.07242943 \n", "3 NEWCOMB ST 42.33418175 -71.07866441 \n", "4 DELHI ST 42.27536542 -71.09036101 \n", "... ... ... ... \n", "319068 COVENTRY ST 42.33695098 -71.08574813 \n", "319069 RIVER ST 42.25592648 -71.12317207 \n", "319070 RIVER ST 42.25592648 -71.12317207 \n", "319071 NEW WASHINGTON ST 42.30233307 -71.11156487 \n", "319072 WASHINGTON ST 42.33383935 -71.08029038 \n", "\n", " Location \n", "0 (42.35779134, -71.13937053) \n", "1 (42.30682138, -71.06030035) \n", "2 (42.34658879, -71.07242943) \n", "3 (42.33418175, -71.07866441) \n", "4 (42.27536542, -71.09036101) \n", "... ... \n", "319068 (42.33695098, -71.08574813) \n", "319069 (42.25592648, -71.12317207) \n", "319070 (42.25592648, -71.12317207) \n", "319071 (42.30233307, -71.11156487) \n", "319072 (42.33383935, -71.08029038) \n", "\n", "[319073 rows x 17 columns]" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import dask\n", "from dask.dataframe import from_delayed\n", "\n", "\n", "def oset(col_name, expr, where):\n", " \n", " where = (where.data[where.cols.names(0)[0]]).to_delayed()\n", " ddf = df.to_delayed()\n", " \n", " def func(_df, _col_name, _mask):\n", " \n", " _df.loc[_mask,[_col_name]]=expr(_df)\n", " return _df\n", "\n", " for _part,_mask in zip(ddf, where):\n", " delayed_parts = dask.delayed(func)(_part, col_name, _mask)\n", "\n", " return from_delayed(delayed_parts)\n", "\n", "col_name=\"INCIDENT_NUMBER\"\n", "where= ((df[col_name]==\"I182070945\") | (df[\"DISTRICT\"]==\"I182070945\"))\n", "F = df.functions\n", "\n", "def expr(series):\n", " return F.lower(series[\"OFFENSE_CODE_GROUP\"])\n", "\n", "\n", "oset(col_name, expr, where).compute()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6" } }, "nbformat": 4, "nbformat_minor": 4 }