= t. tabname and dbsname = "npmdb" and t. tabname not like "sys %" group by 1 having count (*)> 1 order by 2 desc table extent is recommended to have no more than 30. If it is too large, you need to recreate the table and modify the extent size so as to modify the number of indexes in the extent checklist (the fewer the better): select idxname, levels from sysindexes order by 2 desc check index with low hit rate (the closer nrows and unique are, the better): select tabname, idxname, Nrows,
']daily_proxy_visited_count = Daily_proxy_ Data.timestamp.value_counts (). Sort_index () Daily_proxy_visited_count.plot ()For data column discard, in addition to invalid values and requirements, some tables themselves redundant columns also need to be cleaned up in this link, such as the index number in Dataframe, type description, and so on, through the discard of these data, thus generating new data, can make the data capacity effectively reduced, and thus improve the computational efficiency
HDOJ 4259 Double Dealing, hdoj3169
Find the cyclic section of each digit and find the lcm
Double Dealing
Time Limit: 50000/20000 MS (Java/Others) Memory Limit: 32768/32768 K (Java/Others)Total Submission (s): 1806 Accepted Submission (s): 622
Problem DescriptionTake a deck
NUnique cards. Deal the entire deck out
KPlayers in the usual way: the top card to player 1, the next to player 2,
KTh to player
K,
K+ 1st to player 1, and so on. Then pick up th
HDOJ 4259 Double Dealing
Find the cyclic section of each digit and find the lcm
Double Dealing
Time Limit: 50000/20000 MS (Java/Others) Memory Limit: 32768/32768 K (Java/Others)Total Submission (s): 1806 Accepted Submission (s): 622
Problem DescriptionTake a deck
NUnique cards. Deal the entire deck out
KPlayers in the usual way: the top card to player 1, the next to player 2,
KTh to player
K,
K+ 1st to player 1, and so on. Then pick up the cards-pl
modify the number of rows displayed fromPandas import seriess= Series ([0.1,1.2,2.3,3.4,4.5], index = ['a','b','C','D','e']) print s.head (),'\ n'Print S.head (2)A0.1b1.2C2.3D3.4e4.5Dtype:float64 a0.1b1.2Dtype:float642,isnull and notnull return the sequence of equal length,3. Some statistical characteristics of describe return sequence fromPandas import Seriesimport numpy asNPS=series (Np.arange (1.0,Ten) ) S.describe () out[ +]:count9.000000mean5.000000STD2.738613min1.000000 -%3.000000 -%5.0
C # retrieve List data from Sharepoint
C # obtain List data from Sharepoint:
Add reference:
using Microsoft.SharePoint.Client;using System.Data;
Source code:
Public static void getDataFromSPList (string siteURL, string listName) {ClientContext clientContext = new ClientContext (siteURL); Web web = clientContext. web; ListCollection collList = web. lists; clientContext. load (collList); clientContext. executeQuery (); // remote interaction of Sharepoint is executed only after ExecuteQuery. For
Here is still to recommend my own built Python development Learning Group: 483546416, the group is the development of Python, if you are learning Python, small series welcome you to join, everyone is the software Development Party, not regularly share dry goods (only Python software development-related), Including a copy of my own 2018 of the latest Python advanced materials and high-level development tutorials, welcome to the next step and into the small partners who want to dive into python.An
the selection rate valuation has a significant impact on the cost of each execution plan. Therefore, the accuracy of getting the best plan depends entirely on the most recent statistics about the database objects involved in the query.
The following system catalog tables are refreshed whenever the UPDATE STATISTICS query is run. The columns in the table are listed under each heading.
In the Systables
Nindexes-Number of indexes in the table
nrows-Number of rows in the table
npused-Number of
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