I'm trying to convert object to string in my dataframe using pandas. Having following data: particulars NWCLG 545627 ASDASD KJKJKJ ASDASD TGS/ASDWWR42045645010
Well, I have a corpus of 2000+ text documents and I'm trying to make a matrix with pandas dataframe in the most elegant way. The matrix would look like this: d
When Using Streamlit to build a data interface getting a syntax error. My downloaded csv dataframe has a column 'NUMBER OF PERSONS INJURED', after converting i
I have a dataframe and a list df = pd.DataFrame({'A':[1,2,3], 'B':[4,5,6]}) mylist= [10,20,30,40,50] I would like to have a list as element in each row of a
How can lemmatise a dataframe column. CSV file "train.csv" looks like this id tweet 1 retweet if you agree 2 happy birthday your majesty 3 essential oil
I have two identical Spark DataFrame. They have the same columns. I am trying to create a IF-Else statement in one line but couldnt find a better way to do it.
I have a very specific problem to solve that makes researching a solution quite hard because I lack the requisite math skills. My goal: Given a covariance/corre
It seems that dtype only work for pandas.DataFrame.Series, right? Is there a function to display data types of all columns at once?
Lets say I have r = pd.DataFrame({'A':1 , 'B':pd.Series(1,index=list(range(4)),dtype='float32')}) And r['B'].describe()[['mean','std','min','m
Let's say I have a DataFrame that looks like this: df= pd.DataFrame({'A': [1,-2,0,-1,17], 'B': [11,-23,1,-3,132], 'C': [121,
I'm a bit of a beginner when it comes to Python, but one of my projects from school needs me to perform classification algorithms on this reddit popularity data
I have a column Date_Time that I wish to groupby date time without creating a new column. Is this possible the current code I have does not work. df = pd.group
I'm trying to compare two data frames with have same number of columns i.e. 4 columns with id as key column in both data frames df1 = spark.read.csv("/path/to/
I have a data set that has dates and subtotal of other columns. I want to remove the same recurring dates per subtotal
I have a csv file, and want to use H2O to do DeepLearning. But it has some Chinese and datetime that when I finish my Deeplearning need to save output to csv, i
I Have Dataframe with a lot of columns (Around 100 feature), I want to apply the interquartile method and wanted to remove the outlier from the data frame. I a
I have a csv file with below data. Id Subject Marks 1 M,P,C 10,8,6 2 M,P,C 5,7,9 3 M,P,C 6,7,4 I Need to find out Max value in the Marks column for each Id an
I have a reference file like this Id, Value1, Value2 a, a1, a2 b, b1, b2 c, c1, c2 d, d1, d2 ... n, n1, n2 and the missing file Id, Value1, Value2 d, ,
I am trying to pivot the dataframe of raw data size 6 GB and it used to take 30 minutes time (aggregation function sum): x_pivot = raw_df.groupBy("a", "b", "c"
This is a sample dataframe and it containsNA: x y z datetime 0 2 3 4 02-02-2019 1 NA NA NA 03-02-2019 2 3 5 7 04-0