为什么这会返回“太多索引器"? [英] Why does this return 'Too Many Indexers'?

问题描述

我的代码是:

import pandas as pd
import numpy as np
from sklearn import svm

name = '../CLIWOC/CLIWOC15.csv'
data = pd.read_csv(name)

# Get info into dataframe and drop NaNs
data = pd.concat([data.UTC, data.Lon3, data.Lat3, data.Rain]).dropna(how='any')

# Set target
X = data.loc[:, ['UTC', 'Lon3', 'Lat3']]
y = data['Rain']

# Partition a test set
Xtest = X[-1]
ytest = y[-1]
X = X[1:-2]
y = y[1:-2]

# Train classifier
classifier = svm.svc(gamma=0.01, C=100.)
classifier.fit(X, y)
classifier.predict(Xtest)
y

到达设置目标"部分时，编译器返回错误索引器过多".我直接从文档中提取了这个语法，所以我不确定可能有什么问题.csv 使用这些数据列标题进行组织.

Arriving at the 'set target' section, the compiler returns the error 'Too Many Indexers'. I lifted this syntax directly from the documentation, so I'm unsure what could be wrong. The csv is organized with these headers for columns of data.

推荐答案

没有你的数据，很难验证.但是，我立即怀疑您需要传递一个 numpy 数组而不是 DataFrame.

Without your data, it is hard to verify. My immediate suspicion, however, is that you need to pass a numpy array instead of a DataFrame.

试试这个来提取它们:

# Set target
X = data.loc[:, ['UTC', 'Lon3', 'Lat3']].values
y = data['Rain'].values

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