Python 我想从csv文件中获取每一行并存储打印输出,同时获取范围(10)ValueError:';nrows&x27;必须是整数>=0
我想从csv文件中获取每一行并存储打印输出,同时获取范围(10)ValueError:“nrows”必须是整数>=0 作为pd进口熊猫 将numpy作为np导入Python 我想从csv文件中获取每一行并存储打印输出,同时获取范围(10)ValueError:';nrows&x27;必须是整数>=0,python,csv,Python,Csv,我想从csv文件中获取每一行并存储打印输出,同时获取范围(10)ValueError:“nrows”必须是整数>=0 作为pd进口熊猫 将numpy作为np导入 #aaa = pd.read_csv("/content/SolarPrediction_edited.csv", usecols = ['Temperature','Pressure','Humidity','WindDirection(Degrees)','Speed','TSR_Minute','TSS_Min
#aaa = pd.read_csv("/content/SolarPrediction_edited.csv", usecols = ['Temperature','Pressure','Humidity','WindDirection(Degrees)','Speed','TSR_Minute','TSS_Minute','TSS_Hour','Month','Day','Hour','Minute','Second','WindDirection(Degrees)_bin','TSS_Minute_bin','Humidity_bin'])
#aaa.to_csv('/content/SolarPrediction_output.csv')
path="/content/SolarPrediction_output.csv"
#ro=[0,1,2,3,4,5,6,7,8]
for x in range(5):
#print(x)
if x>0:
#print(x)
mydata = pd.read_csv(path, nrows=x)
mydata.drop("Unnamed: 0",axis=1,inplace=True)
df = pd.DataFrame(mydata)
y_pred = np.array(df)
#print(y_pred)
predict=model.predict(y_pred)
print(predict)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-27-25f39d9afdb3> in <module>()
10 if x>0:
11 #print(x)
---> 12 mydata = pd.read_csv(path, nrows=x)
13 mydata.drop("Unnamed: 0",axis=1,inplace=True)
14 df = pd.DataFrame(mydata)
3 frames
/usr/local/lib/python3.7/dist-packages/pandas/io/parsers.py in _validate_integer(name, val, min_val)
391 val = int(val)
392 elif not (is_integer(val) and val >= min_val):
--> 393 raise ValueError(msg)
394
395 return val
ValueError: 'nrows' must be an integer >=0
\aaa=pd.read\u csv(/content/SolarPrediction\u edited.csv),usecols=[‘温度’、‘压力’、‘湿度’、‘风向(度)’、‘速度’、‘TSR_分钟’、‘TSS_分钟’、‘TSS_小时’、‘月’、‘天’、‘小时’、‘分钟’、‘秒’、‘风向(度)_仓’、‘TSS_分钟’、‘湿度_仓’)
#aaa.to_csv('/content/SolarPrediction_output.csv'))
path=“/content/SolarPrediction\u output.csv”
#ro=[0,1,2,3,4,5,6,7,8]
对于范围(5)内的x:
#打印(x)
如果x>0:
#打印(x)
mydata=pd.read\u csv(路径,nrows=x)
mydata.drop(“未命名:0”,轴=1,inplace=True)
df=pd.DataFrame(mydata)
y_pred=np.数组(df)
#打印(y_pred)
预测=模型预测(y_pred)
打印(预测)
---------------------------------------------------------------------------
ValueError回溯(最近一次调用上次)
在()
10如果x>0:
11#打印(x)
--->12 mydata=pd.read\u csv(路径,nrows=x)
13 mydata.drop(“未命名:0”,轴=1,原地=True)
14 df=pd.DataFrame(mydata)
3帧
/usr/local/lib/python3.7/dist-packages/pandas/io/parsers.py in_validate_integer(name,val,min_val)
391 val=int(val)
392 elif not(为整数(val)且val>=最小值):
-->393提升值错误(msg)
394
395返回值
ValueError:“nrows”必须是大于等于0的整数
你应该试试这个,它会起作用的:-
for x in range(1,6):