swifter | efficiently applies any function to a pandas dataframe | Time Series Database library
kandi X-RAY | swifter Summary
kandi X-RAY | swifter Summary
A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner.
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Top functions reviewed by kandi - BETA
- Perform a dask apply
- Apply a function to the DataFrame
- Redirect stdout to stderr
- Wrap a function into a function
- Validate the apply operator
- Register module accessor
- Register a DataFrameAccessor
- Register a parallel series accessor
- Perform the dask apply function
swifter Key Features
swifter Examples and Code Snippets
Lines of Code : 70License : Permissive (MIT)
Copylet TWITTER_CONSUMER_KEY = ""
let TWITTER_CONSUMER_SECRET_KEY = ""
let twitterAccount = ... // An ACAccount instance obtained from ACAccountStore.
let swifter = Swifter(consumerKey: TWITTER_CONSUMER_KEY, consumerSecret: TWITTER_CONSUMER_SECRET_KEY)
License : No LicenseCopy#Training data for chrms 1,3,5,7,9
python example_generate_data_K562_train.py 1,3,5,7,9 contacts.gz
#Validation data for chr 18
python example_generate_data_K562_test.py 18 contacts.gz
DataGenerator: Writing data to file output/K562/chr1_chr3_chr5_c let composedRequest = Before(request).run({ println("Request is fired!") })
let loggedRequest = After(request).run(logger)
df_npy = df.values
input_npy = input.values
df_npy = df_npy / np.linalg.norm(df_npy, axis=1, keepdims=True)
input_npy = input_npy / np.linalg.norm(input_npy, axis=1, keepdims=True)
df_npy @from scipy import stats
df.apply(lambda x: stats.t.interval(0.95, len(x)-1, loc=np.mean(x), scale=stats.sem(x)), axis=1)
import statsmodels.stats.api as sms
df.apply(lambda x: sms.DescrStatsW(x).tconfint_mean(), date = df['Date'].str.replace('0000$','0101')
date = date.str.replace('00$','01')
date = pd.to_datetime(date, format="%Y%m%d")
d1 = pd.to_datetime(df['Date'].str[:-4], format="%Y", errors='coerce')
d2 = pd.to_datetime(df['Date'].str[:-2], format="%Y%m", errors='coerce')
d3 = pd.to_datetime(df['Date'], format="%Y%m%d", errors='coerce')
m1 = df['Date'].str.endswithray.init()
df_ref = ray.put(merged_df)
model_ref = ray.put(classifier)
@ray.remote
def get_meal_category(classifier, df, i, labels, n=3):
seq = df["title"][i]
res_dict = classifier(seq, labels)
return list(zip([seq for i in radef translate_(x):
if x['lang'] != 'en':
text = x['tweet_text']
translated = GoogleTranslator(source='auto', target='en').translate(text)
return translated
df_bdtu['translated_tweet_text'] = df_bdtu.swifter.apply(translate_loc_colname='loc'
weighting_colname='weight'
cat_colname='catvar'
vlength = max(df[loc_colname]+1)
def create sparse vectors(df_temp):
temp_loc_list=df_temp[loc_colname].tolist()
temp_weight=df_temp[weightiCommunity Discussions
Trending Discussions on swifter
QUESTION
Is it possible without using parallelization (Swifter, Parallel) to make an instant calculation immediately without passing through the index, for example through the use of the "apply"-function for all dataset?
...ANSWER
Answered 2022-Feb-19 at 15:05%%time
import random
df = pd.DataFrame({'A':random.sample(range(200), 200)})
QUESTION
I have a very large dataframe (millions of rows) and every time I am getting a 1-row dataframe with the same columns. For example:
...ANSWER
Answered 2022-Jan-24 at 02:31I usually don't do matrix manipulation with DataFrame but with numpy.array. So I will first convert them
QUESTION
If the user is logged-in with the native Twitter app installed, I want my app to open the Twitter app to request authorization.
I already implemented the flow to get the oauth_token in order to start the login process through Twitter's api. Only, the current API Documentation do not mention anything about how to use the native iOS app in the process. It only sends back a url for the user to log in.
ANSWER
Answered 2021-Sep-26 at 17:41This flow seems to have not been officially supported since the retirement of TwitterKit on May 1, 2018. Any applications that still offer this functionality to their end users likely have some sort of partnership with Twitter to allow for this which is otherwise undocumented publicly.
The reasoning for this was detailed sparsely in a related Twitter Developer Forums thread:
Unfortunately at this time we have had to make some incremental adjustments that are not so smooth for everyone; especially as you’ve found, for mobile app developers. We’re in the middle of a transition to a new API platform (via Twitter Developer Labs) and there will be some changes as we go along - we are asking for your feedback to help us, and if you check the ideas, authentication and authorization is something we’ve heard a lot about.
I cannot tell you today exactly when we’ll get to an enhanced solution, but this is something we are actively working on.
The official guidance is to use the traditional WebView method until Twitter officially re-releases this capability:
I don’t believe that this is possible any longer, so I would encourage you to use the full OAuth flow. I apologise that this may not be what your users prefer, but this is the documented way to gain authorisation (we do not document or support URL schemes for the native iOS app).
We do not support or document any means of users signing in to Twitter outside of the OAuth flow; any use of undocumented features is subject to change without notice.
As linked above Twitter appears to be soliciting feedback on this via their UserVoice page, should you feel so inclined to suggest the re-implementation of such a feature.
QUESTION
How to receive an output of an array of [TweetSentimentClassifierInput] objects to send it further to my prediction model?
I have the array but inside a closure which turns it unavailable to return as a method output. If I initialize an empty array outside the closure then the output is always an empty array since fetch closure takes time to be completed.
Code
...ANSWER
Answered 2021-Dec-04 at 08:45Convert this method in async, passing closure with [TweetSentimentClassifierInput] as closure argument, and an error as secondary closure argument,
QUESTION
I'm working with Pandas. I need to create a new column in a dataframe according to conditions in other columns. I try to look for each value in a series if it contains a value (a condition to return text).This works when the values are exactly the same but not when the value is only a part of the value of the series.
...ANSWER
Answered 2021-Oct-22 at 08:09Use numpy.where with Series.str.contains:
QUESTION
I have a pandas dataframe of some 200k records. It has two columns; the text in English and a score. I want to translate a column from English to a few other languages. For that, I'm using the Cloud Translation API from Google's GCP. It's however, taking an absurdly long time to translate them. My code is basically this:
...ANSWER
Answered 2021-Sep-21 at 19:21To fix the slow code, I just initialized the import and translate client outside the function once.
In the case of the 403 POST error, I had to create another GCP account. When I saw the quotas in the old account (trial), nothing was exceeded or close to, but the trial period apparently ended and I didn't have the free credits ($400) anymore. I tried enabling billing for the API (and checked my card wasn't defunct) but that didn't change much. Translate by batch worked in my newer account.
So, it was just an account issue rather than an API issue.
QUESTION
I am create simple rest api with swift using swifter library
How i can response json data?
ANSWER
Answered 2021-Jul-16 at 20:57Use codable and a jsonEncoder to convert the users array to data and then convert them back to a jsonObject and pass it in:
QUESTION
I am working with a Dataframe containing date in string format. Dates look like this: 19620201 so with year first, then month, then day.
I want to convert those dates into Datetime. I tried to use this:
pd.to_datetime(df.Date)
But it doesn't work because some date have the day to "00" sometimes it's the month and sometimes it's even the year.
I don't wanna drop those dates because I still wnat the years or month.
So i tried to write a function like this one:
...ANSWER
Answered 2021-Jun-04 at 07:47First idea is use vectorized solution with pass column to to_datetime and generate ouput column by numpy.where:
QUESTION
I wrote a Dash program using python and it works on Jupyter notebook. But It doesn't work on server. I send my geometric data on server by: scp data.json username@10.0.0.0:/directory
Why in server I cant run this python code:
...ANSWER
Answered 2021-Apr-13 at 20:04Because I want to speed up calculating "norm" , I was used "swifter". It works on PC but it doesn't work on server! After removing that, It works!
QUESTION
I have around 70 categories (it can be 20 or 30 also) and I want to be able to parallelize the process using ray but I get an error:
...ANSWER
Answered 2021-Feb-18 at 01:31This error is happening because of sending large objects to redis. merged_df is a large dataframe and since you are calling get_meal_category 10 times, Ray will attempt to serialize merged_df 10 times. Instead if you put merged_df into the Ray object store just once, and then pass along a reference to the object, this should work.
EDIT: Since the classifier is also large, do something similar for that as well.
Can you try something like this:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install swifter
You can use swifter like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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