小编Nát*_*ali的帖子

我想改善groupby蟒蛇熊猫的时间.我有这个代码:

df["Nbcontrats"] = df.groupby(['Client', 'Month'])['Contrat'].transform(len)

目标是计算客户在一个月内签订的合同数量,并将此信息添加到新列(Nbcontrats)中.

• Client:客户端代码
• Month:数据提取月份
• Contrat: 合同编号

我想改善时间.下面我只使用我的实际数据的一个子集:

%timeit df["Nbcontrats"] = df.groupby(['Client', 'Month'])['Contrat'].transform(len)
1 loops, best of 3: 391 ms per loop

df.shape
Out[309]: (7464, 61)

如何改善执行时间？

我有这个代码

import pandas as pd
import numpy as np
import csv
df = pd.DataFrame({'animal': 'cat dog cat fish dog cat cat'.split(),
               'size': list('SSMMMLL'),
               'weight': [8, 10, 11, 1, 20, 12, 12],
               'adult' : [False] * 5 + [True] * 2}); 

我用NA值改变了重量:

df['weight'] = np.nan

最后我救了它

df.to_csv("ejemplo.csv", sep=";", decimal=",", quoting=csv.QUOTE_NONNUMERIC, index=False)

但是,当我读到文件时,我有"",而不是NA,我想把NA而不是Nan

我想要输出:

adult;animal;size;weight
False;"dog";"S";NA
False;"cat";"M";NA    

我正在使用R中的RecordLinkage Library.我有一个带有id,name,phone,mail的数据框

我的代码看起来像这样:

ids = data$id
pairs = compare.dedup(data, identity=ids, blockfld=as.list(2,3,4))

问题是我的结果输出中的id不同,所以如果我有这些数据:

id   Name     Phone    Mail
233  Nathali  2222     nathali@dd.com
435  Nathali  2222 
553  Jean     3444     jean@dd.com

在我的结果输出中,我会有类似的东西

id1 id2
1   2

代替

id1 id2
233 435 

我想知道是否有办法保留id而不是索引,或者有人可以解释我的身份参数.

谢谢

我有这样的情节::

from bokeh.io import output_file, show
from bokeh.charts import Line
from bokeh.models import FixedTicker
import pandas as pd

output_file('file.html')
data = {'Date shift end': {0: '01/01/16', 1: '01/02/16', 2: '01/03/16',
                           3: '01/04/16', 4: '01/05/16', 5: '01/06/16',
                           6: '01/07/16', 7: '01/08/16', 8: '01/09/16',
                           9: '01/10/16', 10: '01/11/16', 11: '01/12/16',
                           12: '01/13/16', 13: '01/14/16', 14: '01/15/16',
                           15: '01/16/16', 16: '01/17/16', 17: '01/18/16',
                           18: '01/19/16', 19: '01/20/16'},
        'Finance_Lbs': {0: 0.0, 1: 92218.080000000002, 2: 469434.14000000001,
                        3: 513948.95000000001, 4: 578014.71999999997,
                        5: 432396.69, 6: 573912.75,
                        7: …

我有一个scikit-learn安装版本0.18.1 ::

$ pip uninstall -y scipy scikit-learn $ pip install scipy scikit-learn

当我导入GridSearchCV时,我得到一个奇怪的DeprecationWarning ::

(venv2) :~/$ cat warn.pyy
from sklearn.grid_search import GridSearchCV
import sklearn as sk
print(sk.__version__)

如果我运行它我得到::

(venv2) :~/$ python warn.py
/home/n/venv2/local/lib/python2.7/site-packages/sklearn/cross_validation.py:44: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed …