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Import and Export Excel - What is the best library? [closed]
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I'm going to throw my hand in for flat csv files, if only because you've got the greatest control over the code. Just make sure that you read in the rows and process them one at a time (reading the document to the end and splitting will eat up all of your memory -...
How to use the CSV MIME-type?
In a web application I am working on, the user can click on a link to a CSV file. There is no header set for the mime-type, so the browser just renders it as text. I would like for this file to be sent as a .csv file, so the user can directly open it with calc, excel, gnumeric, etc.
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【BLE技术内幕】BLE技术揭秘 - 创客硬件开发 - 清泛IT论坛，有思想、有深度
...参数组在低功耗蓝牙设备的功率优化中起重要作用。以下列表给出了连接参数设置中权衡的总体概述。减少连接间隔如下：增加两个设备的功耗增加双向吞吐量减少任一方向发送数据的时间
增加连接间隔如下：降低两个设备的...
Phpcms v9 实现首页|列表页|内容页点击量调用的代码 - 更多技术 - 清泛网 -...
Phpcms v9 实现首页|列表页|内容页点击量调用的代码1、内容页的点击量获取比较简单，一般默认模板中自带：<span id="hits">< span>...<script language="JavaScript" src="{APP_PATH}api.p...1、内容页的点击量获取比较简单，一般默认模板中自带：
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App Inventor 2 开发多用户注册登录签到系统 - AppInventor连接网络微数据...
...库”如何保存值到网络，如何读取网络值
如何存储用户列表信息
如何存储用户的每日签到列表数据（用户的子对象存储）
aia源码
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注册、登录、签到系统，由于涉及到多用户，需要将每个用户的信息集中存...
Read a zipped file as a pandas DataFrame
I'm trying to unzip a csv file and pass it into pandas so I can work on the file.
The code I have tried so far is:
5 Ans...
How to estimate how much memory a Pandas' DataFrame will need?
I have been wondering... If I am reading, say, a 400MB csv file into a pandas dataframe (using read_csv or read_table), is there any way to guesstimate how much memory this will need? Just trying to get a better feel of data frames and memory...
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csv文件用excel打开修改保存后,日期少了秒 - 更多技术 - 清泛网 - 专注C/C++及内核技术
csv文件用excel打开修改保存后,日期少了秒csv格式的日期打开默认是没有秒的，而且再次保存后秒回丢失，通过设置单元格自定义类型可以解决。选中单元格（或选中列）右键，设置单元格...csv格式的日期打开默认是没有秒的，而...
Can iterators be reset in Python?
...y available.
As several answers rightly remarked, in the specific case of csv you can also .seek(0) the underlying file object (a rather special case). I'm not sure that's documented and guaranteed, though it does currently work; it would probably be worth considering only for truly huge csv file...
Create Pandas DataFrame from a string
...ringIO (python2) or io.StringIO (python3) and pass that to the pandas.read_csv function. E.g:
import sys
if sys.version_info[0] < 3:
from StringIO import StringIO
else:
from io import StringIO
import pandas as pd
TESTDATA = StringIO("""col1;col2;col3
1;4.4;99
2;4.5;200
3;4...