sp500 | S & P500 Daily Data in MySQL , sqlite and CSV formats | Business library
kandi X-RAY | sp500 Summary
kandi X-RAY | sp500 Summary
This is a raw set of imported daily S&P500 CSV data from Yahoo Finance converted to MySQL and sqlite formats. The data is daily open, close, high, low and volume since 3, January 1950.
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QUESTION
I have the following code which generate the following results:
...ANSWER
Answered 2022-Apr-10 at 08:23You are piping the result of your data manipulation through to ggplot, but also passing the name of the data frame as the first argument to ggplot.
Remember that doing
QUESTION
I am trying to put the years 1928 to 2022 into decades categories in R, as I want to calculate the average return of the stock market for each decade
...ANSWER
Answered 2022-Apr-07 at 17:08The labels=
argument to the function you're using accepts a vector of length(breaks)-1
for you to override the labels.
QUESTION
I have a DataFrame like this:
...ANSWER
Answered 2022-Apr-01 at 07:06import pandas as pd
df = pd.read_csv("https://raw.githubusercontent.com/fja05680/sp500/master/S%26P%20500%20Historical%20Components%20%26%20Changes(03-14-2022).csv")
# convert string to list of tickers
df.tickers=df.tickers.str.split(',')
# explode list to rows
df = df.explode("tickers")
# make multi index, order levels and sort
df = df.set_index(['tickers', 'date']).sort_index()
# create random col
df['random value'] = 'x'
QUESTION
getSymbols(c("spy", "XLE", "IYR", "XLP", "XLY", "XLV", "XLK", "XLF", "XLU","IYR","XLI", "XLC", "XME"))
get.sector.performance <- function(interval) {
year <- "2021::"
sp500 <- cumsum(interval(SPY[year]))
}
get.sector.performance(dailyReturn)
...ANSWER
Answered 2022-Mar-03 at 01:53You can use <<-
instead of <-
in order to write an object from a function scope to the global environment.
QUESTION
I have a data Series which looks like this:
...ANSWER
Answered 2022-Feb-20 at 16:31In your code, the wk list is being initialized empty every time, Hence you need to place it outside the loop like below for it to work.
QUESTION
I'm getting data using yahoo_fin. Im Getting the last 100 days from current date. The list tickers_sp500() works but when I try using list tickers_nasdaq(). It keeps throwing timestamp error. I found that it triggers the error when it gets to AGBR from Nasdaq list which only has one row in historical data. In this example Its getting all the data and not just the last 100 but I still get the error. Error is "KeyError: 'timestamp'"
...ANSWER
Answered 2022-Feb-20 at 10:24Ticker data is stored in dictionary-like data structures and those defective tickers (e.g. AGBR
) may be missing the timestamp
key of such dictionary, so it's failing to fetch.
You can skip the defective ones by wrapping the si.get_data
call in a try..except
clause as explained in the Python docs.
In your case, the code would become
QUESTION
I am having difficulty understanding why the apply.quarterly()
function is not really giving me the quarterly returns and returning NA and why my diff(log())
function is also not working with FRED data. Perhaps I am doing something wrong but I cannot really understand what. Could someone help me understand or fix this issue?
The code I use:
...ANSWER
Answered 2022-Feb-14 at 22:07Make these changes:
- do not convert the xts objects to data frames
- suggest not using setDefaults
- n, ns and nd are not used and those lines are dropped.
- add na.rm = TRUE to mean
- use Ad(...) to extract the adjusted column
- have cleaned up formatting
This gives
QUESTION
So I have the monthly returns on the SP500 in addition to the risk free rate in a zoo timeseries object called SP500.df
. I want to backtest two different trading strategies and plot them in a graph. In form of either cumulative return, or just how much 1$ intial investment would be at end of period.
Strategy 1: buy and hold SP500 the whole period.
Strategy 2: Hold SP500 from nov - april (winter), then switch to risk free rate from may - october (summer).
Notice that I also have extracted the winter and summer return in two respective vectors. called Winter_returns
and summer_returns
.
mkt= returns
rf= risk free rate
this is how dataframe SP500.df looks:
...ANSWER
Answered 2022-Feb-07 at 13:11Here is a way.
Define a calculations function calc
and apply it to the column MKT
to have strategy 1 then create a vector of all returns/rates rates
and apply the function to it. The plot uses base R graphics.
QUESTION
I want to store the "info" from a list of the SP500 symbols in a Pandas DataFrame.
I can do this one at a time (df1, df2,...) and then append all into one DataFrame (df):
but would like to have a function that automates this by iterating through a list of symbols and appends new rows each time to 'df'.
Any ideas?? Thanks!
...ANSWER
Answered 2022-Jan-08 at 15:16Try this:
QUESTION
I'm making a bot that takes in the user input (which is a stock symbol) and then provides information on that specific stock. Thing is, I'm not really sure how to use the client.wait_input()
in my case. Here's my code for the bot:
ANSWER
Answered 2022-Jan-02 at 00:16The companySymbol
variable already stores the user's input, so you can modify the stocks_input()
function to take input.
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