{ "cells": [ { "cell_type": "markdown", "metadata": { "collapsed": false }, "source": [ "#### Infiltration Calculations\n", "\n", "Things needed to make calculations more accurate: \n", "- No inf or zeros present in data\n", "- Find true asymtote for CO2_inside (seems to go below 400 \"outside ppm\")\n", "- Get accurate ETC volume. (used 40,000 ft$^3$ here)\n", "- Isolate Negative slopes\n", "- Determine best days/times to isolate further\n", "\n", "\n", "##### VolumetricFlowRate:\n", "\n", "$$CFM_{CO_2} = CFM_{allair} * ( \\% CO_2 outside - \\% CO_2 inside)$$\n", "\n", "$$ VolumetricFlowRate = CFM_{CO_2} / (\\% CO_2 outside - \\% CO_2 inside)$$\n", "- $\\Delta CO_2$ = $CO_2$ cubic feet per minute (cfm)\n", "- Volumetric Flow Rate = Total cubic feet per minute (cfm)\n", "- $CO_2$_outside = proportion (unitless) \n", "- $CO_2$_inside = proportion (unitless) \n", "\n", "\n", "##### Infiltration:\n", "$$ Infiltration = \\frac{\\Delta CO2}{(CO2\\_outside - CO2\\_inside)} * \\frac{1}{Volume} * \\frac{60 min}{hour}$$\n", "\n", "- Infiltration = \"air changes\" Per Minute ($\\large{\\frac{1}{min}}$)\n", "- $\\Delta CO_2$ = $CO_2$ cubic feet per minute (cfm) \n", "- $CO_2$_outside = proportion (unitless) \n", "- $CO_2$_inside = proportion (unitless)\n", "- Volume = ETC cubic feet ( $ft^{3}$ )" ] }, { "cell_type": "code", "execution_count": 57, "metadata": { "collapsed": false }, "outputs": [ ], "source": [ "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": { "collapsed": false }, "source": [ "## More Data Manipulation \n", "\n", "Starting with just ppm and timestamp\n", "\n", "Finshing withing percent CO2 inside and outside, as well as cfm of CO2, and volume of ETC." ] }, { "cell_type": "code", "execution_count": 58, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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CO2Time
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" ] }, "execution_count": 58, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df1 = pd.read_csv('NetatmoCleanedForInfiltrationAnalysis.csv', parse_dates=True)\n", "df1.drop(df1.columns[[0]], axis =1 , inplace = True)\n", "df1.head()" ] }, { "cell_type": "code", "execution_count": 59, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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CO2Time
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" ] }, "execution_count": 59, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df1['Time'] = pd.to_datetime(df1.Time)\n", "df1.head()" ] }, { "cell_type": "code", "execution_count": 60, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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ppm_insideTime
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" ] }, "execution_count": 60, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df1.rename(index=str, columns={\"CO2\": \"ppm_inside\"}, inplace = True)\n", "df1.head()" ] }, { "cell_type": "code", "execution_count": 61, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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ppm_insideTimeTimeDeltappm_outsideETC_Volumechangeinppminside
0718.02016-02-19 13:27:00NaN40040000.0NaN
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3328.02016-02-19 13:41:005.040040000.0-4.0
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" ] }, "execution_count": 61, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df1['TimeDelta'] = df1['Time'].diff(1)\n", "df1['TimeDelta'] = df1.TimeDelta / np.timedelta64(1, 'm')\n", "df1['ppm_outside'] = 400\n", "df1['ETC_Volume'] = 4e4\n", "df1['changeinppminside'] = df1['ppm_inside'].diff(1)\n", "df1.head(4)" ] }, { "cell_type": "markdown", "metadata": { "collapsed": false }, "source": [ "Cfm = percent change inside * Volume of ETC" ] }, { "cell_type": "code", "execution_count": 62, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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ppm_insideTimeTimeDeltappm_outsideETC_Volumechangeinppminsidepercentchangeinside
0718.02016-02-19 13:27:00NaN40040000.0NaNNaN
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" ] }, "execution_count": 62, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df1['percentchangeinside'] = df1['changeinppminside'] / 1e4\n", "df1.head()" ] }, { "cell_type": "code", "execution_count": 63, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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ppm_insideTimeTimeDeltappm_outsideETC_VolumechangeinppminsidepercentchangeinsideCFM_CO2
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" ] }, "execution_count": 63, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df1['CFM_CO2'] = (df1['percentchangeinside'] / df1['TimeDelta'])* df1['ETC_Volume']\n", "df1.head()" ] }, { "cell_type": "code", "execution_count": 64, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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ppm_insideTimeTimeDeltappm_outsideETC_VolumechangeinppminsidepercentchangeinsideCFM_CO2percent_Insidepercent_Outside
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4307.02016-02-19 13:46:005.040040000.0-21.0-0.0021-16.80.03070.04
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" ] }, "execution_count": 64, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df1['percent_Inside'] = df1['ppm_inside'] / 1e4\n", "df1['percent_Outside'] = df1['ppm_outside'] / 1e4\n", "df1.head()" ] }, { "cell_type": "code", "execution_count": 65, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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TimeETC_VolumeCFM_CO2percent_Insidepercent_Outside
02016-02-19 13:27:0040000.0NaN0.07180.04
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" ] }, "execution_count": 65, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df1.drop(df1.columns[[0, 2, 3, 5, 6,]], axis =1 , inplace = True)\n", "df1.head()" ] }, { "cell_type": "code", "execution_count": 66, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "count 100985.000000\n", "mean 0.054765\n", "std 0.030451\n", "min 0.020100\n", "25% 0.036200\n", "50% 0.043800\n", "75% 0.061500\n", "max 0.277700\n", "Name: percent_Inside, dtype: float64" ] }, "execution_count": 66, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df1.percent_Inside.describe()" ] }, { "cell_type": "code", "execution_count": 67, "metadata": { "collapsed": false }, "outputs": [ ], "source": [ "df1.to_csv('InfiltrationFINALCleanedData.csv')" ] }, { "cell_type": "code", "execution_count": 68, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "Time 2016-02-19 16:07:00\n", "ETC_Volume 40000\n", "CFM_CO2 12.8\n", "percent_Inside 0.0409\n", "percent_Outside 0.04\n", "Name: 32, dtype: object" ] }, "execution_count": 68, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df2 = pd.read_csv('InfiltrationFINALCleanedData.csv', parse_dates=True, index_col=0)\n", "df2.iloc[32]" ] }, { "cell_type": "code", "execution_count": 69, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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ETC_VolumeCFM_CO2percent_Insidepercent_Outside
count13010.013010.00000013010.0000001.301000e+04
mean40000.0-10.7771210.0957514.000000e-02
std0.018.0903600.0313188.195149e-15
min40000.0-498.4000000.0601004.000000e-02
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50%40000.0-6.4000000.0897004.000000e-02
75%40000.0-3.2000000.1110004.000000e-02
max40000.0-0.4083710.2733004.000000e-02
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" ] }, "execution_count": 69, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df2 = df2[df2['percent_Inside']>(df2['percent_Outside'] + 0.02)]\n", "df2 = df2[df2['CFM_CO2'] < 0]\n", "df2 = df2.replace([np.inf, -np.inf], np.nan)\n", "df2.dropna()\n", "df2.describe()" ] }, { "cell_type": "code", "execution_count": 70, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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TimeETC_VolumeCFM_CO2percent_Insidepercent_Outside
8442016-02-22 12:12:0040000.0-54.40.08160.04
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" ] }, "execution_count": 70, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df2.head()" ] }, { "cell_type": "code", "execution_count": 71, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 71, "metadata": { }, "output_type": "execute_result" }, { "data": { "image/png": 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}, "execution_count": 71, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df2['CFM_CO2'].hist(bins = 50, range = (-80, 0))" ] }, { "cell_type": "code", "execution_count": 72, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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ETC_VolumeCFM_CO2percent_Insidepercent_OutsideCFM_ETC
count13010.013010.00000013010.0000001.301000e+0413010.000000
mean40000.0-10.7771210.0957514.000000e-02-230.943259
std0.018.0903600.0313188.195149e-15394.273245
min40000.0-498.4000000.0601004.000000e-02-16950.495050
25%40000.0-12.0000000.0693254.000000e-02-261.949742
50%40000.0-6.4000000.0897004.000000e-02-136.850291
75%40000.0-3.2000000.1110004.000000e-02-65.573770
max40000.0-0.4083710.2733004.000000e-02-4.208311
\n", "
" ] }, "execution_count": 72, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df2['CFM_ETC'] = df2['CFM_CO2'] / (df2['percent_Inside'] - df2['percent_Outside'])\n", "df2.describe()" ] }, { "cell_type": "code", "execution_count": 73, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 73, "metadata": { }, "output_type": "execute_result" }, { "data": { "image/png": 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" }, "execution_count": 73, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df2['CFM_ETC'].plot()" ] }, { "cell_type": "code", "execution_count": 101, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 101, "metadata": { }, "output_type": "execute_result" }, { "data": { "image/png": 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ETC_VolumeCFM_CO2percent_Insidepercent_OutsideCFM_ETCACH
count13010.013010.00000013010.0000001.301000e+0413010.00000013010.000000
mean40000.0-10.7771210.0957514.000000e-02-230.943259-0.346415
std0.018.0903600.0313188.195149e-15394.2732450.591410
min40000.0-498.4000000.0601004.000000e-02-16950.495050-25.425743
25%40000.0-12.0000000.0693254.000000e-02-261.949742-0.392925
50%40000.0-6.4000000.0897004.000000e-02-136.850291-0.205275
75%40000.0-3.2000000.1110004.000000e-02-65.573770-0.098361
max40000.0-0.4083710.2733004.000000e-02-4.208311-0.006312
\n", "
" ] }, "execution_count": 75, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df2['ACH'] = (df2['CFM_ETC'] / df2['ETC_Volume']) * 60\n", "df2.describe()" ] }, { "cell_type": "code", "execution_count": 100, "metadata": { "collapsed": false }, "outputs": [ ], "source": [ "#df2['CFM_ETC'].plot.density( range = 200 )" ] }, { "cell_type": "code", "execution_count": 77, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 77, "metadata": { }, "output_type": "execute_result" }, { "data": { "image/png": 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" }, "execution_count": 77, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df2['ACH'].hist(bins = 10, range = (-10, 0))" ] }, { "cell_type": "code", "execution_count": 78, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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ETC_VolumeCFM_CO2percent_Insidepercent_OutsideCFM_ETCACH
Time
2016-02-22 12:12:0040000.0-54.40.08160.04-1307.692308-1.961538
2016-02-22 12:22:0040000.0-4.80.08250.04-112.941176-0.169412
2016-02-22 12:27:0040000.0-16.80.08040.04-415.841584-0.623762
2016-02-22 12:32:0040000.0-12.00.07890.04-308.483290-0.462725
2016-02-22 12:37:0040000.0-22.40.07610.04-620.498615-0.930748
\n", "
" ] }, "execution_count": 78, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df2.set_index('Time',inplace=True)\n", "df2.head()" ] }, { "cell_type": "code", "execution_count": 79, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 79, "metadata": { }, "output_type": "execute_result" }, { "data": { "image/png": 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" }, "execution_count": 79, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df2['ACH'].plot()" ] }, { "cell_type": "code", "execution_count": 80, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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TimeETC_VolumeCFM_CO2percent_Insidepercent_OutsideCFM_ETCACH
02016-02-22 12:12:0040000.0-54.40.08160.04-1307.692308-1.961538
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" ] }, "execution_count": 80, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df2.reset_index(inplace = True)\n", "df2.head(1)" ] }, { "cell_type": "code", "execution_count": 81, "metadata": { "collapsed": false }, "outputs": [ ], "source": [ "df2['Time'] = pd.to_datetime(df2.Time)" ] }, { "cell_type": "code", "execution_count": 82, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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TimeETC_VolumeCFM_CO2percent_Insidepercent_OutsideCFM_ETCACHDay
02016-02-22 12:12:0040000.0-54.40.08160.04-1307.692308-1.961538Monday
12016-02-22 12:22:0040000.0-4.80.08250.04-112.941176-0.169412Monday
22016-02-22 12:27:0040000.0-16.80.08040.04-415.841584-0.623762Monday
32016-02-22 12:32:0040000.0-12.00.07890.04-308.483290-0.462725Monday
42016-02-22 12:37:0040000.0-22.40.07610.04-620.498615-0.930748Monday
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" ] }, "execution_count": 82, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df2['Day'] = df2.Time.dt.weekday_name\n", "df2.head()" ] }, { "cell_type": "code", "execution_count": 83, "metadata": { "collapsed": false }, "outputs": [ ], "source": [ "#df3.Day.value_counts()" ] }, { "cell_type": "code", "execution_count": 84, "metadata": { "collapsed": false }, "outputs": [ ], "source": [ "InfiltrationData = df2.drop(df2.columns[[1,2,3,4,5]], axis =1 )\n", "InfiltrationData.to_csv('FinalData.csv')" ] }, { "cell_type": "code", "execution_count": 85, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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TimeACHDay
02016-02-22 12:12:00-1.961538Monday
12016-02-22 12:22:00-0.169412Monday
22016-02-22 12:27:00-0.623762Monday
32016-02-22 12:32:00-0.462725Monday
42016-02-22 12:37:00-0.930748Monday
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" ] }, "execution_count": 85, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df3 = pd.read_csv('FinalData.csv', index_col = 0, parse_dates=True)\n", "df3.head()" ] }, { "cell_type": "code", "execution_count": 86, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "Time object\n", "ACH float64\n", "Day object\n", "dtype: object" ] }, "execution_count": 86, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df3.dtypes" ] }, { "cell_type": "code", "execution_count": 87, "metadata": { "collapsed": false }, "outputs": [ ], "source": [ "df3['Time'] = pd.to_datetime(df2.Time)\n", "#df3['Day'] = pd.to_datetime(df2.Time)" ] }, { "cell_type": "code", "execution_count": 88, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "Time datetime64[ns]\n", "ACH float64\n", "Day object\n", "dtype: object" ] }, "execution_count": 88, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df3.dtypes" ] }, { "cell_type": "code", "execution_count": 89, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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ACH
count1645.000000
mean-1.167449
std0.755820
min-4.958678
25%-1.273469
50%-0.871972
75%-0.708861
max-0.600000
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" ] }, "execution_count": 89, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df3 = df3[df3['ACH'] < -0.6]\n", "df3 = df3[df3['ACH'] > -5.0]\n", "df3.describe()" ] }, { "cell_type": "code", "execution_count": 90, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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TimeACHDay
02016-02-22 12:12:00-1.961538Monday
22016-02-22 12:27:00-0.623762Monday
42016-02-22 12:37:00-0.930748Monday
82016-02-22 13:03:00-0.766667Monday
102016-02-22 13:13:00-1.320388Monday
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" ] }, "execution_count": 90, "metadata": { }, "output_type": "execute_result" } ], "source": [ "df3.head()" ] }, { "cell_type": "code", "execution_count": 91, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 91, "metadata": { }, "output_type": "execute_result" }, { "data": { "image/png": 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" }, "execution_count": 91, "metadata": { }, "output_type": "execute_result" } ], "source": [ "Fridays = df3[df3['Day'] == 'Friday']\n", "Fridays.set_index('Time',inplace=True)\n", "Fridays.plot()" ] }, { "cell_type": "code", "execution_count": 92, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 92, "metadata": { }, "output_type": "execute_result" }, { "data": { "image/png": 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" }, "execution_count": 92, "metadata": { }, "output_type": "execute_result" } ], "source": [ "Tuesdays = df3[df3['Day'] == 'Tuesday']\n", "Tuesdays.set_index('Time',inplace=True)\n", "Tuesdays.plot()" ] }, { "cell_type": "code", "execution_count": 93, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([[]],\n", " dtype=object)" ] }, "execution_count": 93, "metadata": { }, "output_type": "execute_result" }, { "data": { "image/png": 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}, "execution_count": 93, "metadata": { }, "output_type": "execute_result" } ], "source": [ "Fridays.hist(bins = 100, range = (-2 , -0.5))" ] }, { "cell_type": "code", "execution_count": 94, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([[]],\n", " dtype=object)" ] }, "execution_count": 94, "metadata": { }, "output_type": "execute_result" }, { "data": { "image/png": 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" }, "execution_count": 94, "metadata": { }, "output_type": "execute_result" } ], "source": [ "Tuesdays.hist(bins = 100, range = (-2 , -0.5))" ] }, { "cell_type": "code", "execution_count": 95, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 95, "metadata": { }, "output_type": "execute_result" }, { "data": { "image/png": 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" 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max-0.600000
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