2 Hour Taxi Ride Cost

Taxicab 1 mile (normal fare), £2.36, 1.93-3.22. For this purpose, we have decided to track a typical price range of 3 kilometers (about 2 miles) travel in each destination. Costs for a 3-kilometer taxi ride in 88 major cities.

How much does a ride cost? {\a6}(1 of 2) (NYC Taxi fare)

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"Meta data": "_uuuid": "b32848a9a584034368d3d0bb4ef32574d93e947c", "cell_type": "markdown", "source": "# Data Loading and Preparation\nThis data set is so huge that we can easily allow only those lines to fall that we don't like. Take everyone with a ticket price below 0 away. Your taxi chauffeur won't buy you!

Take away all ride that have more than 6 passangers, I don't think that more than that really fits into a taxi..... Taxis are probably scheduled for the weekday, the daytime and much more. Normalize after uploading all files to memory", "Metadata": "_kg_Hide-Output": :, "_kg_hide-input" :, "Trusted" :, "_uuuid" :

"This is the 370bb2add2a4d6f0e4beff08ca172c2d3a59b416", "Collapses":, "cell_type": "code", "source": "# thanks to formula for this rapid charging method\ndef file_len(fname):\n \n < n sub-process. Meta data": "trustworthy":, "_uuuid": "6aa0f86aab6d25e807982c025eb725b50e65cd4b", "_kg_hide-output" :, "_kg_hide-input" :, "collapsed" :, "cell_type" : "code", "source" :

Meta data": "trustworthy":, "_uuuid": "4fc4d00a96a0e50f69ea8265ea76a4a7c5b929", "_kg_hide-output" :, "_kg_hide-input" :, "collapsed" :, "cell_type" : "code", "source" : We have so much information that we can afford removing the zeros, df.drop(df[df.isnull().any(1)]. index, axis=0, inplace=True)\n \n < 2.

df.drop(df[df[df. fare_amount < MIN_FARE]. index, axis=0, place=True )\n < df.drop(df[df. fare_amount > MAX_FARE]. index, axis=0, inplace=True)\n < #3. Fare_amount > MAX_FARE df.drop(df[df. number of passengers > MAX_PASSENGER]. index, axle = 0, inplace=True)\n \n df.drop(df[df. number of passengers < MIN_PASSENGER]. index, axle = 0, inplace=True)\n < # 4.

index, axis=0, enplace=True )\n \n df.drop(df[df[df. pickup_latitude < LAT_MIN]. index, axis=0, enplace=True ]\n df.drop(df. pickup_latitude < LAT_MIN), index, axis=0, inplace=True]\n\n enplace=True × enlace_MAX), et alto.df

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Meta data": "trustworthy":, "_uuuid": "5b13eca649564bc7e93d96a8ac62254e6fb859b7", "_kg_hide-output":, "_kg_hide-input":, "cell_type":, "code", "source": "# Combine all data frames into one dataframe\nX = pd. Meta data": "_uuuid": "5dc8aebc6ef9d1884e2aa0dae2014b44a7cb5fcf", "cell_type": "markdown", "source": "# Visualize the Data\n\n**Red** Diagrams are for the moment.

" Meta data": "_uuuid": "3a2a937c47b9640fe5ca49aa1194196a6d59a77d", "cell_type": "markdown", "source": "## How many persons drive at the same moment? "Meta data": "trusted":, "_uuuid": "e2c0f13610a55027b4b1bbc5390adfeb13f2b7f7", "_kg_hide input" :, "cell_type" : "code", "source" : "# Number of Passengers vs. Fare Amount\nplt. Metadata": and " _kg_hide-output": and "_kg_hide-input": and "_kg_hide-input": and "trusted": and "_uuuid": and "b453072bae7051ec9f1db8f469ee148ee13f0723" and "cell_type": and "code" and "source": and "# cleanup\ndel p1\ndel p2\ndel p3\ndel p4\ndel p5\ndel p5\ndel p2\ndel p3\ndel p4\ndel p5\ndel.

Meta data": "_uuuid": "c94c70060ca7260d8165597b81a651cea32f55dc", "cell_type": "markdown", "source": "There are far more individual drivers than any other number. "Meta data": "_uuuid": "36cfd63d93677028831499f8f2bc9b37102a62e", "cell_type": "markdown", "source": "## What kind of day do humans take with them? "MetaDaten" : "_kg_hide-input":: :, "vertrauenswürdig" :, "_uuuuuuid" : "facb7e7f130b02cf340d4c0b478a30bafe75a691", "cell_type" : "code", "source" : "# Day of the Week vs Fare Amount\nplt.

Meta data" : "_kg_Hide-Output" :, "_kg_Hide-Input" :, "Trusted" :, "_uuuid" : "699d964f28e6c015e23a7871876b93ae7121fced", "cell_type" : "{\a6} Code", "Source": "# cleanup\ndel mon\ndel tue\ndel wed\ndel thu\ndel fri\ndel sat\ndel sun\ngc. Meta data": "_uuuid": "295da7390f53ced6b493076ece027504be8a12", "cell_type": "markdown", "source": "The number of passengers rises gradually during the course of the weekly period, starts as low on Sunday and reaches a maximum on Saturday at the highest passenger number.

The costs are about the same regardless of the weekday. "Meta data": "_uuuid": "78f453520ab11387bf4b76a3fc6e03e88618a953", "cell_type": "markdown", "source": "## Where do they come from and where do they go", "metadata" : "The following options are available: "_kg_hide-input" :, "Trusted" :, "_uuuid" : "00265851c713541ed2a9f6bfb8ae7b418e5ee5dd", "cell_type" : "code", "source" : "plt.

Meta data": "_uuuid": "41fb2f6e52daa708111c6285064bd8ac6e84c6b8", "cell_type": "markdown", "source": "## How far do they go and how much do they pay? "Meta data": "trustworthy":, "_uuuid": "27cb5b96b1086256571aae775011c3544b2d52d1", "_kg_hide-input" :, "cell_type" : "code", "source" : "# Hour vs. Fare Amount\nplt.

"Meta data": "_uuuid": "a7278536fc7ea42a7959f3d1d058410229f83673", "cell_type": "markdown", "source": "## How far do humans travel?

" Meta data": "_kg_hide-input"::, "trusted":, "_uuuid": "7973ec04b97846bc490b331fa89deb091276b3b8", "cell_type" : "code", "source" : "plt.figure()\nplt. hist (X., "metadata": "_uuuid": "7405f931f18ab4676f50c9a659455a5e693712e4", "cell_type": "markdown", "source": "This is a little unanticipated spreading. "Meta data": "_uuuid": "cc541b21efc73f77ca25b0733afb9e77d9457c0c", "cell_type": "markdown", "source" : "## How much does it cost to travel the route?

" Meta data": "trustworthy":, "_uuuid": "97f9db8705fd0ef3db5cc5cf752132e1438e5bad", "_kg_hide-input" :, "cell_type" : "code", "source" : "# Fare vs Distance\nplt.

There is a general tendency, as you would think, the further the journey: the higher the cost. \n", "Metadata" : "kernelspec" : "display_name" : "Python 3", "language" : "python", "name" : "python3", "language_info" :