Python pd.read_csv 中的字符串行索引导致错误“标签 [1] 不在 [索引] 中”
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String row-index in pd.read_csv causes error "The label [1] is not in the [index]"
提问by Rupert
I am importing a CSV into a pandas dataframe. When I am do this, I am setting the index column to 0, which is the Index listed (0 to 10). I am getting the error Key Error: the label [1] is not in the [index].
我正在将 CSV 导入到 Pandas 数据框中。当我这样做时,我将索引列设置为 0,即列出的索引(0 到 10)。我收到错误密钥错误:标签 [1] 不在 [索引] 中。
I've checked the data multiple times to make sure that the first column is the list of numbers. Any hints on how I can fix this?
我已经多次检查数据以确保第一列是数字列表。关于如何解决这个问题的任何提示?
from __future__ import division
import pandas as pd
import random
import math
#USER VARIABLES
#GAME VARIABLES
Passengers = 500
data = pd.read_csv("Problem2/data.csv", index_col=0)
print(data)
obs = len(data)
data["A"] = 0
data["B"] = 0
data["U"] = 0
for row in range(1,obs+1, 1):
A = 0
B = 0
U = 0
for i in range(1, Passengers + 1, 1):
if data.loc[row, i] == "A":
A += 1
elif data.loc[row, i] == "B":
B += 1
else:
U += 1
data.loc[row, "A"] = A
data.loc[row, "B"] = B
data.loc[row, "U"] = U
ServiceLevels = range(170, 210,1)
for level in ServiceLevels:
print(str(level) + " " + str(len(data[((data.A <= level))])/obs))
Dataset = https://github.com/deacons2016/SimulationModels/blob/master/Exam1/Problem2/data.csv
数据集 = https://github.com/deacons2016/SimulationModels/blob/master/Exam1/Problem2/data.csv
采纳答案by Alexis G
You have to cast columns with str
in your for.
你必须str
在你的 for 中投射列。
In[60]: data = pd.read_csv(r'/Users/Desktop/data.csv', sep = ',', index_col = [0])
In[61]: obs = len(data)
In[62]: data["A"] = 0
data["B"] = 0
data["U"] = 0
In[63]: Passengers = 500
In[64]: for row in range(1,obs+1):
print row
A = 0
B = 0
U = 0
for i in range(1, Passengers + 1, 1):
if data.loc[row, str(i)] == "A":
A += 1
elif data.loc[row, str(i)] == "B":
B += 1
else:
U += 1
data.loc[row, "A"] = A
data.loc[row, "B"] = B
data.loc[row, "U"] = U
1
.
.
10
A shortest way to do that :
一个最短的方法来做到这一点:
data = pd.read_csv(r'/Users/Desktop/data.csv', sep = ',', index_col = [0])
cols = data.columns
data['A'] = (data[cols] == 'A').astype(int).sum(axis=1)
data['B'] = (data[cols] == 'B').astype(int).sum(axis=1)
data['U'] = (data[cols] == 'U').astype(int).sum(axis=1)