{ "metadata": { "name": "", "signature": "sha256:55609d0e101015296bd00c16afe3c0e3be54e593a7088092d40a32f3e006d1ac" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "code", "collapsed": false, "input": [ "import numpy as np\n", "import pandas as pd \n", "from pandas import Series, DataFrame" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 2 }, { "cell_type": "code", "collapsed": false, "input": [ "# Lets make Series\n", "ser1 = Series([1,2,3,4,1,2,3,4])\n", "#Show\n", "ser1" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 3, "text": [ "0 1\n", "1 2\n", "2 3\n", "3 4\n", "4 1\n", "5 2\n", "6 3\n", "7 4\n", "dtype: int64" ] } ], "prompt_number": 3 }, { "cell_type": "code", "collapsed": false, "input": [ "# Using replace we can select --> .replace(value to be replaced, new_value)\n", "ser1.replace(1,np.nan)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 4, "text": [ "0 NaN\n", "1 2\n", "2 3\n", "3 4\n", "4 NaN\n", "5 2\n", "6 3\n", "7 4\n", "dtype: float64" ] } ], "prompt_number": 4 }, { "cell_type": "code", "collapsed": false, "input": [ "#Can also input lists\n", "ser1.replace([1,4],[100,400])" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 5, "text": [ "0 100\n", "1 2\n", "2 3\n", "3 400\n", "4 100\n", "5 2\n", "6 3\n", "7 400\n", "dtype: int64" ] } ], "prompt_number": 5 }, { "cell_type": "code", "collapsed": false, "input": [ "#Can also input dictionary\n", "ser1.replace({4:np.nan})" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 15, "text": [ "0 1\n", "1 2\n", "2 3\n", "3 NaN\n", "4 1\n", "5 2\n", "6 3\n", "7 NaN\n", "dtype: float64" ] } ], "prompt_number": 15 }, { "cell_type": "code", "collapsed": false, "input": [ "#That's it for replace, next up Renaming an axis index" ], "language": "python", "metadata": {}, "outputs": [] } ], "metadata": {} } ] }