Question

我有一个字典，里面填充了我导入的两个文件中的数据，但有些数据是以nan形式出现的。如何使用nan删除数据？

我的代码是：

import matplotlib.pyplot as plt 
from pandas.lib import Timestamp
import numpy as np   
from datetime import datetime
import pandas as pd
import collections

orangebook = pd.read_csv('C:\Users\WEGWEIS_JAKE\Desktop\Work Programs\Code Files\products2.txt',sep='~', parse_dates=['Approval_Date'])
specificdrugs=pd.read_csv('C:\Users\WEGWEIS_JAKE\Desktop\Work Programs\Code Files\Drugs.txt',sep=',')

"""This is a dictionary that collects data from the .txt file
This dictionary has a key,value pair for every generic name with its corresponding approval date """
drugdict={}
for d in specificdrugs['Generic Name']:
    drugdict.dropna()
    drugdict[d]=orangebook[orangebook.Ingredient==d.upper()]['Approval_Date'].min()

我应该添加或删除此代码以确保字典中没有值为nan的键值对？

Answer 1

from math import isnan

如果将nans存储为密钥：

# functional
clean_dict = filter(lambda k: not isnan(k), my_dict)

# dict comprehension
clean_dict = {k: my_dict[k] for k in my_dict if not isnan(k)}

如果将nans存储为值：

# functional
clean_dict = filter(lambda k: not isnan(my_dict[k]), my_dict)

# dict comprehension
clean_dict = {k: my_dict[k] for k in my_dict if not isnan(my_dict[k])}

Answer 2

使用simplejson

import simplejson

clean_dict  = simplejson.loads(simplejson.dumps(my_dict, ignore_nan=True))
## or depending on your needs
clean_dict  = simplejson.loads(simplejson.dumps(my_dict, allow_nan=False))

Answer 3

您应该进一步调查为什么NaN会首先到达那里，而不是尝试从字典中删除NaN。

在字典中使用NaN很困难，因为NaN不等于自己。

查看此信息以获取更多信息：NaNs as key in dictionaries

Answer 4

知道老了，但这对我有用，很简单-预先阅读CSV即可删除NaN：

orangebook = pd.read_csv('C:\Users\WEGWEIS_JAKE\Desktop\Work Programs\Code Files\products2.txt',sep='~', parse_dates=['Approval_Date']).dropna()

我也想同时转换成字典：

orangebook = pd.read_csv('C:\Users\WEGWEIS_JAKE\Desktop\Work Programs\Code Files\products2.txt',sep='~', parse_dates=['Approval_Date']).dropna().to_dict()

有没有办法从填充数据的字典中删除nan？

4 个答案: