bhf | admin interface for trusted user | Dashboard library
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kandi X-RAY | bhf Summary
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QUESTION
I have a list containing some text data.
When I used pd.DataFrame to put in the list I cannot see the whole data.
...ANSWER
Answered 2021-Mar-03 at 13:10Have a look at:
Pretty-print an entire Pandas Series / DataFrame
Pandas doesn't print long lines and cuts of the line after some symbols. Most of the time, this is not a problem, except you have entries with huge sizes.
QUESTION
I am trying to put text inside SVG so we can use custom fonts in PowerApps
Sp I have an image with the below definition in the Image property (I've cut out the Base 64 font definition of about 1000 lines:
...ANSWER
Answered 2020-Feb-25 at 18:24I would calculate the size of the text using javascript like so:
QUESTION
From a big Dataframe with info from tennis players, I created a df with only backhand shots from a single player, which includes columns with names, age and "x,y" coordinates of where the shots where taken. I already made a graphic with the tennis court and the places where the shots where taken, but I´m having a hard time creating the convex hull.
To create the first graphic I used:
...ANSWER
Answered 2020-Jan-15 at 21:36BH = data.frame(x = rnorm(2000), y= rnorm(2000)) # create a dummy example data.frame
BHL = chull(BH[, c("x", "y")]) # calculate convex hull for x and y columns
BHL = c(BHL, BHL[1]) # add the first point again at the end, so the path loops back to the beginning
#now plot using geom_path
ggplot(BH, aes(x,y)) +
geom_point() +
geom_path(data=BH[BHL, ])
QUESTION
I want to search for locations in a searchview and display the location on a map with a marker. When the marker is clicked, I want to show a infowindow with the location name, etc. I use OSMDROID and the OSMBONUSPACK.
The Problem:
The marker is shown as intented and its onClickListener does fire, but the infowindow is not shown if I call my searchLocationOnMap from onQueryTextSubmit. How to fix that?
Does not work(no info window shown if marker is clicked):
...ANSWER
Answered 2020-Jan-02 at 10:41I solve it with something like this
QUESTION
I am trying to find specific strings in a directory of PDF files by first using this regex to search the document for everything that looks like a string, and then comparing it to an existing list of known strings:
regex = "\\b(?:" + "|".join(symbols) + ")\\b"
The code works if I am scanning sample text within the program itself. But when I loop through the PDFs, I get re.error: nothing to repeat at position 23457. So it seems as though one of the characters isn't being escaped properly, but I can't figure out which.
Here is my code:
...ANSWER
Answered 2019-Apr-24 at 14:41Some of your symbols contain characters that have special meaning in regular expressions. * and + are used to indicate repetition of the preceding pattern. One of your symbols has one of these with no pattern before it, so there's nothing for it to repeat. If you look around position 23457 of the regexp, you should see the symbol that caused the problem.
Use re.escape() when creating the regexp, to make all the special characters be treated literally.
QUESTION
My aim is to download stock prices using the quantmod library for a large number of ticker symbols (~700) and merge the results in a single dataframe which I will save as a csv file. I have a list of ticker symbols but not all of them are downloadable by quantmod.
So when I pass the list with the ticker symbols to the getSymbols() method, once it encounters a problem with a particular ticker symbol it stops and returns an exception. I am trying to circumvent this behavior with a for loop and the try method, but I fail.
Let's look at some code:
When I try to download two ticker symbols that are downloadable and then merge them into one xts object I succeed:
...ANSWER
Answered 2019-Apr-18 at 08:59Here is a code I tried. It seems working (although I tried only a subset of the vector):
QUESTION
import pandas as pd
import requests
from bs4 import BeautifulSoup
from datetime import datetime
import pandas_datareader.data as web
tickers
['MMM', 'ABT', 'ABBV', 'ACN', 'ATVI', 'AYI', 'ADBE', 'AMD', 'AAP', 'AES', 'AET', 'AMG', 'AFL', 'A', 'APD', 'AKAM', 'ALK', 'ALB', 'ARE', 'ALXN', 'ALGN', 'ALLE', 'AGN', 'ADS', 'LNT', 'ALL', 'GOOGL', 'GOOG', 'MO', 'AMZN', 'AEE', 'AAL', 'AEP', 'AXP', 'AIG', 'AMT', 'AWK', 'AMP', 'ABC', 'AME', 'AMGN', 'APH', 'APC', 'ADI', 'ANDV', 'ANSS', 'ANTM', 'AON', 'AOS', 'APA', 'AIV', 'AAPL', 'AMAT', 'APTV', 'ADM', 'ARNC', 'AJG', 'AIZ', 'T', 'ADSK', 'ADP', 'AZO', 'AVB', 'AVY', 'BHGE', 'BLL', 'BAC', 'BK', 'BAX', 'BBT', 'BDX', 'BRK.B', 'BBY', 'BIIB', 'BLK', 'HRB', 'BA', 'BWA', 'BXP', 'BSX', 'BHF', 'BMY', 'AVGO', 'BF.B', 'CHRW', 'CA', 'COG', 'CDNS', 'CPB', 'COF', 'CAH', 'CBOE', 'KMX', 'CCL', 'CAT', 'CBG', 'CBS', 'CELG', 'CNC', 'CNP', 'CTL', 'CERN', 'CF', 'SCHW', 'CHTR', 'CHK', 'CVX', 'CMG', 'CB', 'CHD', 'CI', 'XEC', 'CINF', 'CTAS', 'CSCO', 'C', 'CFG', 'CTXS', 'CLX', 'CME', 'CMS', 'KO', 'CTSH', 'CL', 'CMCSA', 'CMA', 'CAG', 'CXO', 'COP', 'ED', 'STZ', 'COO', 'GLW', 'COST', 'COTY', 'CCI', 'CSRA', 'CSX', 'CMI', 'CVS', 'DHI', 'DHR', 'DRI', 'DVA', 'DE', 'DAL', 'XRAY', 'DVN', 'DLR', 'DFS', 'DISCA', 'DISCK', 'DISH', 'DG', 'DLTR', 'D', 'DOV', 'DWDP', 'DPS', 'DTE', 'DRE', 'DUK', 'DXC', 'ETFC', 'EMN', 'ETN', 'EBAY', 'ECL', 'EIX', 'EW', 'EA', 'EMR', 'ETR', 'EVHC', 'EOG', 'EQT', 'EFX', 'EQIX', 'EQR', 'ESS', 'EL', 'ES', 'RE', 'EXC', 'EXPE', 'EXPD', 'ESRX', 'EXR', 'XOM', 'FFIV', 'FB', 'FAST', 'FRT', 'FDX', 'FIS', 'FITB', 'FE', 'FISV', 'FLIR', 'FLS', 'FLR', 'FMC', 'FL', 'F', 'FTV', 'FBHS', 'BEN', 'FCX', 'GPS', 'GRMN', 'IT', 'GD', 'GE', 'GGP', 'GIS', 'GM', 'GPC', 'GILD', 'GPN', 'GS', 'GT', 'GWW', 'HAL', 'HBI', 'HOG', 'HRS', 'HIG', 'HAS', 'HCA', 'HCP', 'HP', 'HSIC', 'HSY', 'HES', 'HPE', 'HLT', 'HOLX', 'HD', 'HON', 'HRL', 'HST', 'HPQ', 'HUM', 'HBAN', 'HII', 'IDXX', 'INFO', 'ITW', 'ILMN', 'IR', 'INTC', 'ICE', 'IBM', 'INCY', 'IP', 'IPG', 'IFF', 'INTU', 'ISRG', 'IVZ', 'IQV', 'IRM', 'JEC', 'JBHT', 'SJM', 'JNJ', 'JCI', 'JPM', 'JNPR', 'KSU', 'K', 'KEY', 'KMB', 'KIM', 'KMI', 'KLAC', 'KSS', 'KHC', 'KR', 'LB', 'LLL', 'LH', 'LRCX', 'LEG', 'LEN', 'LUK', 'LLY', 'LNC', 'LKQ', 'LMT', 'L', 'LOW', 'LYB', 'MTB', 'MAC', 'M', 'MRO', 'MPC', 'MAR', 'MMC', 'MLM', 'MAS', 'MA', 'MAT', 'MKC', 'MCD', 'MCK', 'MDT', 'MRK', 'MET', 'MTD', 'MGM', 'KORS', 'MCHP', 'MU', 'MSFT', 'MAA', 'MHK', 'TAP', 'MDLZ', 'MON', 'MNST', 'MCO', 'MS', 'MOS', 'MSI', 'MYL', 'NDAQ', 'NOV', 'NAVI', 'NTAP', 'NFLX', 'NWL', 'NFX', 'NEM', 'NWSA', 'NWS', 'NEE', 'NLSN', 'NKE', 'NI', 'NBL', 'JWN', 'NSC', 'NTRS', 'NOC', 'NCLH', 'NRG', 'NUE', 'NVDA', 'ORLY', 'OXY', 'OMC', 'OKE', 'ORCL', 'PCAR', 'PKG', 'PH', 'PDCO', 'PAYX', 'PYPL', 'PNR', 'PBCT', 'PEP', 'PKI', 'PRGO', 'PFE', 'PCG', 'PM', 'PSX', 'PNW', 'PXD', 'PNC', 'RL', 'PPG', 'PPL', 'PX', 'PCLN', 'PFG', 'PG', 'PGR', 'PLD', 'PRU', 'PEG', 'PSA', 'PHM', 'PVH', 'QRVO', 'PWR', 'QCOM', 'DGX', 'RRC', 'RJF', 'RTN', 'O', 'RHT', 'REG', 'REGN', 'RF', 'RSG', 'RMD', 'RHI', 'ROK', 'COL', 'ROP', 'ROST', 'RCL', 'CRM', 'SBAC', 'SCG', 'SLB', 'SNI', 'STX', 'SEE', 'SRE', 'SHW', 'SIG', 'SPG', 'SWKS', 'SLG', 'SNA', 'SO', 'LUV', 'SPGI', 'SWK', 'SBUX', 'STT', 'SRCL', 'SYK', 'STI', 'SYMC', 'SYF', 'SNPS', 'SYY', 'TROW', 'TPR', 'TGT', 'TEL', 'FTI', 'TXN', 'TXT', 'TMO', 'TIF', 'TWX', 'TJX', 'TMK', 'TSS', 'TSCO', 'TDG', 'TRV', 'TRIP', 'FOXA', 'FOX', 'TSN', 'UDR', 'ULTA', 'USB', 'UAA', 'UA', 'UNP', 'UAL', 'UNH', 'UPS', 'URI', 'UTX', 'UHS', 'UNM', 'VFC', 'VLO', 'VAR', 'VTR', 'VRSN', 'VRSK', 'VZ', 'VRTX', 'VIAB', 'V', 'VNO', 'VMC', 'WMT', 'WBA', 'DIS', 'WM', 'WAT', 'WEC', 'WFC', 'HCN', 'WDC', 'WU', 'WRK', 'WY', 'WHR', 'WMB', 'WLTW', 'WYN', 'WYNN', 'XEL', 'XRX', 'XLNX', 'XL', 'XYL', 'YUM', 'ZBH', 'ZION', 'ZTS']
data_source = 'google'
start='2017-01-01'
end = '2018-01-01'
for i in tickers:
web.DataReader(i, data_source, start, end).to_csv(i+'.csv')
ANSWER
Answered 2018-Feb-22 at 11:17Well, for some reason, Google don't seem to have the day-series price data for Lockheed Martin for 2017 (the ticker symbol your query failed on.)
Also, Google don't like automated queries on financial data: if I run your code I regularly get a response including the text "We're sorry... but your computer or network may be sending automated queries. To protect our users, we can't process your request right now."
If you just want the price data, one simple answer is to use Yahoo instead. Here's a test program (based on your code) that I ran on Yahoo, to check for how many of your symbols it could supply price data:
QUESTION
I'm working on text analysis in Python, I'm looking at a range of Irish language texts dating from the 6th century to the 14th, which means I have a whole range of orthographic variations to account for when sorting a word list.
I want to sort a list which takes into account different grammatical forms of characters (e.g. fada, séimhiú, and úru) from different periods by their core words, so my custom alphabet will look like this:
"a, á, b, ḃ, bh, mb, c, ċ, ch, gc, d, ḋ, dh, nd, e, é, f, ḟ, fh, bhf, g, ġ, gh, ng, h, i, í, l, m, ṁ, mh, n, o, ó, p, ṗ, ph, bp, r, rh, s, ṡ, sh, t, ṫ, th, ts, dt, u, ú, j, k, q, v, w, x, y, z"
I can probably handle the fada (accented letters) with Unicode encoding, e.g u'á', but I'm struggling to find a way to work with the old style úru (diacritic dot)?
Does anyone have experience with this sort of mix of characters? Is there a common way that people have developed to work with these characters?
Currently when ever I try to use a diacritic dot charcter with u'ḃ' I get the following error:
...ANSWER
Answered 2018-Mar-08 at 17:57The problem as shown is printing a character that isn't supported by your code page (cp850). You can manipulate Unicode strings just fine...it's just a problem of display. Python 3.6+ solves this issue by bypassing code pages and printing using Windows Unicode APIs:
QUESTION
Piggy backing off my own previous question python pandas: assign control vs. treatment groupings randomly based on %
Thanks to @maxU, I know how to assign random control/treatment groupings to 2 groups; but what if I have 3 groups or more?
For example:
...ANSWER
Answered 2017-Oct-03 at 20:01In [13]: df
Out[13]:
customer_id Group
0 ABC 1
1 CDE 3
2 BHF 2
3 NID 1
4 WKL 3
5 SDI 2
6 JSK 1
7 OSM 3
8 MPA 2
9 MAD 1
In [14]: d = {1:[.5,.5], 2:[.4,.6], 3:[.2,.8]}
In [15]: df['Flag'] = \
...: df.groupby('Group')['customer_id'] \
...: .transform(lambda x: np.random.choice(['Control','Test'], len(x), p=d[x.name]))
...:
In [16]: df
Out[16]:
customer_id Group Flag
0 ABC 1 Control
1 CDE 3 Test
2 BHF 2 Test
3 NID 1 Control
4 WKL 3 Control
5 SDI 2 Test
6 JSK 1 Test
7 OSM 3 Test
8 MPA 2 Control
9 MAD 1 Test
QUESTION
I am working on an experiment design, where I need to split a dataframe df into a control and treatment group by % by pre-existing groupings.
This is the dataframe df:
...ANSWER
Answered 2017-Oct-03 at 20:00we can use numpy.random.choice() method:
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