I´m currently using a tool, which creates a little informational report over solidity smart contracts with some usefull informations in it, that I want to partially display on the website I´m working on.
The tool is called solidity-metrics (https://github.com/ConsenSys/solidity-metrics) and can be used as CLI or as a library in your backend for example, which is what I want to use.
I´m sending files to my backend, which than scans those solidity files with the metrics tool.
It creates can create an object with a lot of meta-data using metrics.total() but it also can create a markdown string using metrics.generateReportMarkdown().
It includes taledata, which is only displayed in the markdown, not in the metrics.total() object, so I need to somehow turn it into html.
The table content from the markdown looks like this:
| Type | File | Logic Contracts | Interfaces | Lines | nLines | nSLOC | Comment Lines | Complex. Score | Capabilities |
|========|=================|============|=======|=======|===============|==============|
| 📝 | ./uploads/contracts/ProjectName.sol | 1 | **** | 564 | 535 | 308 | 152 | 221 | **<abbr title='Uses Assembly'>🖥</abbr><abbr title='Payable Functions'>💰</abbr><abbr title='Uses Hash-Functions'>🧮</abbr><abbr title='create/create2'>🌀</abbr>** |
| 📝 | ./uploads/contracts/ERC2981.sol | 1 | **** | 48 | 37 | 24 | 7 | 15 | **** |
| 🔍 | ./uploads/contracts/IERC2981.sol | **** | 1 | 18 | 14 | 3 | 10 | 3 | **** |
| 📝 | ./uploads/contracts/MockERC721.sol | 1 | **** | 27 | 27 | 19 | 1 | 18 | **** |
| 📝 | ./uploads/contracts/TokenName.sol | 1 | **** | 285 | 262 | 157 | 46 | 159 | **<abbr title='Uses Assembly'>🖥</abbr><abbr title='Uses Hash-Functions'>🧮</abbr>** |
| 📝 | ./uploads/contracts/Originals.sol | 1 | **** | 142 | 128 | 83 | 22 | 81 | **<abbr title='Uses Hash-Functions'>🧮</abbr>** |
| 📝 | ./uploads/contracts/SutterTreasury.sol | 1 | **** | 23 | 23 | 17 | 1 | 20 | **<abbr title='Payable Functions'>💰</abbr>** |
| 📝🔍 | **Totals** | **6** | **1** | **1107** | **1026** | **611** | **239** | **517** | **<abbr title='Uses Assembly'>🖥</abbr><abbr title='Payable Functions'>💰</abbr><abbr title='Uses Hash-Functions'>🧮</abbr><abbr title='create/create2'>🌀</abbr>** |
What I´ve tried and found out so far:
So the table actually kinda looks like normal markdown to me, but somehow, when trying to throw it inside a .md files it still doesn´t look like it should:
I figured out, that they have linked this github.css file in their credits:
https://gist.github.com/tuzz/3331384
tryed to import it into the .md file but it also didn´t seem to work, don´t even know if that makes sense to import a css file into a .md file...
To come to an end, does anyone have an idea on how to turn this markdown into html, which looks like the image I posted above (which I created with the function, which you can build into vs code, where you can mark the files, right click and scan them using metrics)?
Edit: So I figured out, that the equal signs, splitting the headers from the table body could be replaced by hyphens, which would work out fine in the markdown. I could solve that by replacing all "=" with "-", but that would destroy the rest of the markdown file, because there are also other usecases for the equal sign.
I'm trying to use the Merge() function in RStudio. Basically I have two tables with 5000+ rows. They both have the same amount of rows. Although there is no corresponding Columns to merge by. However the rows are in order and correspond. E.g. The first row of dataframe1 should merge with first row dataframe2...2nd row dataframe1 should merge with 2nd row dataframe2 and so on...
Here's an example of what they could look like:
Dataframe1(df1):
+-------------------------------------+
| Name | Sales | Location |
+-------------------------------------+
| Rod | 123 | USA |
| Kelly | 142 | CAN |
| Sam | 183 | USA |
| Joyce | 99 | NED |
+-------------------------------------+
Dataframe2(df2):
+---------------------+
| Sex | Age |
+---------------------+
| M | 23 |
| M | 33 |
| M | 31 |
| F | 45 |
+---------------------+
NOTE: this is a downsized example only.
I've tried to use the merge function in RStudio, here's what I've done:
DFMerged <- merge(df1, df2)
This however increases both the rows and columns. It returns 16 rows and 5 columns for this example.
What am I missing from this function, I know there is a merge(x,y, by=) argument but I'm unable to use a column to match them.
The output I would like is:
+----------------------------------------------------------+
| Name | Sales | Location | Sex | Age |
+----------------------------------------------------------+
| Rod | 123 | USA | M | 23 |
| Kelly | 142 | CAN | M | 33 |
| Sam | 183 | USA | M | 31 |
| Joyce | 99 | NED | F | 45 |
+-------------------------------------+--------------------+
I've considering making extra columns in each dataframes, says row# and match them by that.
You could use cbind:
cbind(df1, df2)
If you want to use merge you could use:
merge(df1, df2, by=0)
You could use:
cbind(df1,df2)
This will necessarily work with same number of rows in two data frames
I have the following table in an sqlite database
+----+-------------+-------+
| ID | Week Number | Count |
+----+-------------+-------+
| 1 | 1 | 31 |
| 2 | 2 | 16 |
| 3 | 3 | 73 |
| 4 | 4 | 59 |
| 5 | 5 | 44 |
| 6 | 6 | 73 |
+----+-------------+-------+
I want to get the following table out. Where I get this weeks sales as one column and then the next column will be last weeks sales.
+-------------+-----------+-----------+
| Week Number | This_Week | Last_Week |
+-------------+-----------+-----------+
| 1 | 31 | null |
| 2 | 16 | 31 |
| 3 | 73 | 16 |
| 4 | 59 | 73 |
| 5 | 44 | 59 |
| 6 | 73 | 44 |
+-------------+-----------+-----------+
This is the select statement i was going to use:
select
id, week_number, count,
(select count from tempTable
where week_number = (week_number-1))
from
tempTable;
You are comparing values in two different rows. When you are just writing week_number, the database does not know which one you mean.
To refer to a column in a specific table, you have to prefix it with the table name: tempTable.week_number.
And if both tables have the same name, you have to rename at least one of them:
SELECT id,
week_number,
count AS This_Week,
(SELECT count
FROM tempTable AS T2
WHERE T2.week_number = tempTable.week_number - 1
) AS Last_Week
FROM tempTable;
In case of you want to take a query upon a same table twice, you have to put aliases on the original one and its replicated one to differentiate them
select a.week_number,a.count this_week,
(select b.count from tempTable b
where b.week_number=(a.week_number-1)) last_week
from tempTable a;
I am copying csv file to cassandra. I have the below csv file and the table is created as below.
CREATE TABLE UCBAdmissions(
id int PRIMARY KEY,
admit text,
dept text,
freq int,
gender text
)
When I use
copy UCBAdmissions from 'UCBAdmissions.csv' WITH DELIMITER = ',' AND HEADER = TRUE;
The output is
24 rows imported in 0.318 seconds.
cqlsh> select *from UCBAdmissions;
id | admit | dept | freq | gender
----+-------+------+------+--------
(0 rows)
copy UCBAdmissions(id,admit,gender, dept , freq )from 'UCBAdmissions.csv' WITH DELIMITER = ',' AND HEADER = TRUE;
The output is
24 rows imported in 0.364 seconds.
cqlsh> select *from UCBAdmissions;
id | admit | dept | freq | gender
----+----------+------+------+--------
23 | Admitted | F | 24 | Female
5 | Admitted | B | 353 | Male
10 | Rejected | C | 205 | Male
16 | Rejected | D | 244 | Female
13 | Admitted | D | 138 | Male
11 | Admitted | C | 202 | Female
1 | Admitted | A | 512 | Male
19 | Admitted | E | 94 | Female
8 | Rejected | B | 8 | Female
2 | Rejected | A | 313 | Male
4 | Rejected | A | 19 | Female
18 | Rejected | E | 138 | Male
15 | Admitted | D | 131 | Female
22 | Rejected | F | 351 | Male
20 | Rejected | E | 299 | Female
7 | Admitted | B | 17 | Female
6 | Rejected | B | 207 | Male
9 | Admitted | C | 120 | Male
14 | Rejected | D | 279 | Male
21 | Admitted | F | 22 | Male
17 | Admitted | E | 53 | Male
24 | Rejected | F | 317 | Female
12 | Rejected | C | 391 | Female
3 | Admitted | A | 89 | Female
UCBAdmissions.csv
"","Admit","Gender","Dept","Freq"
"1","Admitted","Male","A",512
"2","Rejected","Male","A",313
"3","Admitted","Female","A",89
"4","Rejected","Female","A",19
"5","Admitted","Male","B",353
"6","Rejected","Male","B",207
"7","Admitted","Female","B",17
"8","Rejected","Female","B",8
"9","Admitted","Male","C",120
"10","Rejected","Male","C",205
"11","Admitted","Female","C",202
"12","Rejected","Female","C",391
"13","Admitted","Male","D",138
"14","Rejected","Male","D",279
"15","Admitted","Female","D",131
"16","Rejected","Female","D",244
"17","Admitted","Male","E",53
"18","Rejected","Male","E",138
"19","Admitted","Female","E",94
"20","Rejected","Female","E",299
"21","Admitted","Male","F",22
"22","Rejected","Male","F",351
"23","Admitted","Female","F",24
"24","Rejected","Female","F",317
I see the output order getting changed from the csv file as seen above.
Question: What is the difference between 1 and 2? Should we follow the same order as of csv file to create the table in cassandra?
Cassandra is designed to be distributed - to accomplish this, it uses the partition key of your table (id) and hashes it using the cluster's partitioner (probably Murmur3Partitioner) to create an integer (actually a Long), and then uses that integer to assign it to a node in the ring.
What you're seeing are the results ordered by the resulting token, which is non-intuitive, but not necessarily wrong. There is no straight-forward way to do a SELECT * FROM table ORDER BY primaryKey ASC in Cassandra - the distributed nature makes that difficult to do effectively.
Just starting out with R and trying to figure out what works for my needs when it comes to creating "summary tables." I am used to Custom Tables in SPSS, and the CrossTable function in the package gmodels gets me almost where I need to be; not to mention it is easy to navigate for someone just starting out in R.
That said, it seems like the Hmisc table is very good at creating various summaries and exporting to LaTex (ultimately what I need to do).
My questions are:1)can you create the table below easily in the Hmsic page? 2) if so, can I interact variables (2 in the the column)? and finally 3) can I access p-values of significance tests (chi square).
Thanks in advance,
Brock
Cell Contents
|-------------------------|
| Count |
| Row Percent |
| Column Percent |
|-------------------------|
Total Observations in Table: 524
| asq[, 23]
asq[, 4] | 1 | 2 | 3 | 4 | 5 | Row Total |
-------------|-----------|-----------|-----------|-----------|-----------|-----------|
0 | 76 | 54 | 93 | 46 | 54 | 323 |
| 23.529% | 16.718% | 28.793% | 14.241% | 16.718% | 61.641% |
| 54.286% | 56.250% | 63.265% | 63.889% | 78.261% | |
-------------|-----------|-----------|-----------|-----------|-----------|-----------|
1 | 64 | 42 | 54 | 26 | 15 | 201 |
| 31.841% | 20.896% | 26.866% | 12.935% | 7.463% | 38.359% |
| 45.714% | 43.750% | 36.735% | 36.111% | 21.739% | |
-------------|-----------|-----------|-----------|-----------|-----------|-----------|
Column Total | 140 | 96 | 147 | 72 | 69 | 524 |
| 26.718% | 18.321% | 28.053% | 13.740% | 13.168% | |
-------------|-----------|-----------|-----------|-----------|-----------|-----------|
The gmodels package has a function called CrossTable, which is very nice for those used to SPSS and SAS output. Try this example:
library(gmodels) # run install.packages("gmodels") if you haven't installed the package yet
x <- sample(c("up", "down"), 100, replace = TRUE)
y <- sample(c("left", "right"), 100, replace = TRUE)
CrossTable(x, y, format = "SPSS")
This should provide you with an output just like the one you displayed on your question, very SPSS-y. :)
If you are coming from SPSS, you may be interested in the package Deducer ( http://www.deducer.org ). It has a contingency table function:
> library(Deducer)
> data(tips)
> tables<-contingency.tables(
+ row.vars=d(smoker),
+ col.vars=d(day),data=tips)
> tables<-add.chi.squared(tables)
> print(tables,prop.r=T,prop.c=T,prop.t=F)
================================================================================================================
==================================================================================
========== Table: smoker by day ==========
| day
smoker | Fri | Sat | Sun | Thur | Row Total |
-----------------------|-----------|-----------|-----------|-----------|-----------|
No Count | 4 | 45 | 57 | 45 | 151 |
Row % | 2.649% | 29.801% | 37.748% | 29.801% | 61.885% |
Column % | 21.053% | 51.724% | 75.000% | 72.581% | |
-----------------------|-----------|-----------|-----------|-----------|-----------|
Yes Count | 15 | 42 | 19 | 17 | 93 |
Row % | 16.129% | 45.161% | 20.430% | 18.280% | 38.115% |
Column % | 78.947% | 48.276% | 25.000% | 27.419% | |
-----------------------|-----------|-----------|-----------|-----------|-----------|
Column Total | 19 | 87 | 76 | 62 | 244 |
Column % | 7.787% | 35.656% | 31.148% | 25.410% | |
Large Sample
Test Statistic DF p-value | Effect Size est. Lower (%) Upper (%)
Chi Squared 25.787 3 <0.001 | Cramer's V 0.325 0.183 (2.5) 0.44 (97.5)
-----------
================================================================================================================
You can get the counts and test to latex or html using the xtable package:
> library(xtable)
> xtable(drop(extract.counts(tables)[[1]]))
> test <- contin.tests.to.table((tables[[1]]$tests))
> xtable(test)