我试图找出为什么如果我减去两组数据它会给我NaN错误。我想做一个逐个元素的减法，我已经成功地提取了两个单独的集合但是当我尝试用它做任何事情时，它一直给我NaN错误
这是我的代码：
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
filename = 'vc_test.csv'
headings = 'injection', 'treatment','filename', 'l0', 'l1', 'l2', 'l3', 'filename', 'r0', 'r1', 'r2', 'r3'
#import data
df = pd.read_csv(filename, names=headings)
#convert values to floats
df['l0'] = df['l0'].astype(float)
df['l1'] = df['l1'].astype(float)
df['l2'] = df['l2'].astype(float)
df['l3'] = df['l3'].astype(float)
df['r0'] = df['r0'].astype(float)
df['r1'] = df['r1'].astype(float)
df['r2'] = df['r2'].astype(float)
df['r3'] = df['r3'].astype(float)
#group by injection so you have 2 subgroups
df.groupby(['injection'])
#subtract and assign to a different array to normalize data to baseline
df_os, df_od = df[['l1','l2','l3']].sub(df['l0'], axis=0), df[['r1','r2','r3']].sub(df['r0'], axis=0)
print df_os
print df_od
ioc = df_os - df_od
print ioc
我也试过df.sub（）但它没有用。请帮忙......
答案 0 :(得分：0)
列名称存在问题 - 您需要在减去DataFrames两者中使用相同的列名称。同样，对于创建DataFrames，您可以使用boolean indexing。
import pandas as pd
import io
temp=u"""
1,a1453905960,a,95.4500,95.0900,95.0980,433810,s,95.4500,95.0900,95.0980,433810
1,a1453906020,b,95.4700,94.9500,95.4500,934980,d,85.4520,94.100,95.7980,433810
2,a1453906080,f,95.1000,94.8700,95.0900,791657,e,95.4500,934980,9.4400,85.4520
2,a1453906140,c,4.0300,94.7000,94.9620,763531,w,95.1000,94.8700,95.0900,791657
2,a1453906200,f,95.0300,94.8200,94.8918,501298,r,95.1000,94.8700,95.0900,791657"""
headings =[ 'injection', 'treatment','filename', 'l0', 'l1', 'l2', 'l3', 'filename', 'r0', 'r1', 'r2', 'r3']
#after testing replace io.StringIO(temp) to filename
df = pd.read_csv(io.StringIO(temp), names=headings)
print df
injection treatment filename l0 l1 l2 l3 filename \
0 1 a1453905960 s 95.45 95.09 95.0980 433810 s
1 1 a1453906020 d 95.47 94.95 95.4500 934980 d
2 2 a1453906080 e 95.10 94.87 95.0900 791657 e
3 2 a1453906140 w 4.03 94.70 94.9620 763531 w
4 2 a1453906200 r 95.03 94.82 94.8918 501298 r
r0 r1 r2 r3
0 95.450 95.09 95.098 433810.000
1 85.452 94.10 95.798 433810.000
2 95.450 934980.00 9.440 85.452
3 95.100 94.87 95.090 791657.000
4 95.100 94.87 95.090 791657.000
#convert values to floats
df[['l0','l1','l2','l3','r0','r1','r2','r3']] = df[['l0','l1','l2','l3','r0','r1','r2','r3']].astype(float)
#select data by column injection to 2 new dataframes by boolean indexing
df_os = df[df['injection'] == 1]
#print df_os
df_od = df[df['injection'] == 2]
#print df_od
#subtract and assign to a different array to normalize data to baseline
df_os, df_od = df[['l1','l2','l3']].sub(df['l0'], axis=0), df[['r1','r2','r3']].sub(df['r0'], axis=0)
print df_os
l1 l2 l3
0 -0.36 -0.3520 433714.55
1 -0.52 -0.0200 934884.53
2 -0.23 -0.0100 791561.90
3 90.67 90.9320 763526.97
4 -0.21 -0.1382 501202.97
print df_od
r1 r2 r3
0 -0.360 -0.352 433714.550
1 8.648 10.346 433724.548
2 934884.550 -86.010 -9.998
3 -0.230 -0.010 791561.900
4 -0.230 -0.010 791561.900
#set column names in df_od by df_os
df_od.columns = df_os.columns
ioc = df_os - df_od
print ioc
l1 l2 l3
0 0.000 0.0000 0.000
1 -9.168 -10.3660 501159.982
2 -934884.780 86.0000 791571.898
3 90.900 90.9420 -28034.930
4 0.020 -0.1282 -290358.930
ioc = df_os.sub(df_od)
print ioc
l1 l2 l3
0 0.000 0.0000 0.000
1 -9.168 -10.3660 501159.982
2 -934884.780 86.0000 791571.898
3 90.900 90.9420 -28034.930
4 0.020 -0.1282 -290358.930
或者您可以DataFrames将numpy arrays转换为ioc = df_os.values - df_od.values
print ioc
[[ 0.00000000e+00 0.00000000e+00 0.00000000e+00]
[ -9.16800000e+00 -1.03660000e+01 5.01159982e+05]
[ -9.34884780e+05 8.60000000e+01 7.91571898e+05]
[ 9.09000000e+01 9.09420000e+01 -2.80349300e+04]
[ 2.00000000e-02 -1.28200000e-01 -2.90358930e+05]]
print pd.DataFrame(ioc, columns=['a','b','c'])
a b c
0 0.000 0.0000 0.000
1 -9.168 -10.3660 501159.982
2 -934884.780 86.0000 791571.898
3 90.900 90.9420 -28034.930
4 0.020 -0.1282 -290358.930
，然后减去：
$add_image=$_FILES["add_image"]["name"];
if($add_image)
{
$extension = getExtension($add_image);
$extension = strtolower($extension);
if (($extension != "jpg") && ($extension != "jpeg") && ($extension != "png") && ($extension != "gif"))
{
echo "Unknown Image extension";
}
else
{
$size=filesize($_FILES['add_image']['tmp_name']);
if($extension=="jpg" || $extension=="jpeg" )
{
$uploadedfile = $_FILES['file']['tmp_name'];
$src = imagecreatefromjpeg($uploadedfile);
}
else if($extension=="png")
{
$uploadedfile = $_FILES['file']['tmp_name'];
$src = imagecreatefrompng($uploadedfile);
}
else
{
$src = imagecreatefromgif($uploadedfile);
}
list($width,$height)=getimagesize($uploadedfile);
$newwidth=500;
$newheight=($height/$width)*$newwidth;
$tmp=imagecreatetruecolor($newwidth,$newheight);
$newwidth1=300;
$newheight1=($height/$width)*$newwidth1;
$tmp1=imagecreatetruecolor($newwidth1,$newheight1);
imagecopyresampled($tmp,$src,0,0,0,0,$newwidth,$newheight,$width,$height);
imagecopyresampled($tmp1,$src,0,0,0,0,$newwidth1,$newheight1,$width,$height);
//$filename = "images/". $_FILES['file']['name'];
}
$rand = rand(0,999);
$rename_image = $rand.'_'.$add_image;
$uploaddir = 'admin/pages/images/'.$upload_sale.'/';
$uploadfile = $uploaddir . $add_image;
imagejpeg($tmp,$uploadfile,100);
imagejpeg($tmp1,$uploadfile,100);
imagedestroy($src);
imagedestroy($tmp);
imagedestroy($tmp1);