How to send a pandas dataframe to a hive table? I know if I have a spark dataframe, I can register it to a temporary table using df.registerTempTable("table_
I'm starting a work to analyse data from Stats Institutions like Eurostat using python, and so pandas. I found out there are two methods to get data from Eurost
Suppose I have pandas DataFrame like this: df = pd.DataFrame({'id':[1,1,1,2,2,2,2,3,4],'value':[1,2,3,1,2,3,4,1,1]}) which looks like: id value 0 1
Is there a better way to determine whether a variable in Pandas and/or NumPy is numeric or not ? I have a self defined dictionary with dtypes as keys and nume
Given the following DataFrame of pandas in Python: | ID | date | |--------------|------------------------------------
I have a very large dataframe (around 1 million rows) with data from an experiment (60 respondents). I would like to split the dataframe into 60 dataframes (a d
I have a dataframe with names that I set to a dictionary, like this: {1: "Bob", 41: "John", 126: "Jim", 167: "Pete"} I am using Vertica. I want to be able to p
I have a dataframe with names that I set to a dictionary, like this: {1: "Bob", 41: "John", 126: "Jim", 167: "Pete"} I am using Vertica. I want to be able to p
I tried titanic model on kaggle. And it is weird that isna().sum() outputs wrong information. import os import pandas as pd import numpy as np import statsmode
Maybe a silly question. I have been trying to use dt accessor in pandas to use datetime methods on certain date fields in my Data Frame. Not sure why, but the a
I was counting the no of occurrence of angle and dist by the code below: g = new_df.value_counts(subset=['Current_Angle','Current_dist'] ,sort = False) the out
I am doing an analysis of a dataset with 6 classes, zero based. The dataset is many thousands of items long. I need two dataframes with classes 0 & 1 fo
Pandas lets you pass an AWS S3 path directly to .to_csv() and .to_parquet(). There's a storage_options argument for passing S3 specific arguments. I would like
I have several GB of CSV files where values in one of the columns look like this: Which is a consequence of this: urls.append(re.findall(r'http\S+', hashtags_r
I'm trying to use pandas to manipulate a .csv file but I get this error: pandas.parser.CParserError: Error tokenizing data. C error: Expected 2 fields in li
all_data['Title']= all_data['Name'].str.split(', ', expand=True)[1].str.split('.', expand=True)[0] Can anyone explain what is the meaning of this line of code?
I need convert the data stored in a pandas.DataFrame into a byte string where each column can have a separate data type (integer or floating point). Here is a
I have a function which looks like below. def some_func(df:pd.Dataframe=pd.Dataframe()): if not df or df.empty: //some dataframe operations I want to ens
I ran these codes a while ago and it worked but now there is a ValueError: protocol not known. Could anyone help. Thanks. import json temp = json.dumps([status.
What is the most efficient way to organise the following pandas Dataframe: data = Position Letter 1 a 2 b 3 c 4 d 5