Hi there, I am using the following line of Code to get a DataFrame Output using Pandas :- import pandas as pd import requests from bs4 import BeautifulSoup import numpy as np import datetime as dt class work: def __init__(self,link): ...
Seriously? How do you not see this? The error message told you exactly what is wrong. Your date format specifier is '%d-%m-%y'. It's looking for a string with the values IN ORDER: day, month, year. The date string you're passing in is day, YEAR,...
The KeyError is because you are using the boolean value True as an index into the date_col_search list in line 15. So change your code from line 13 on to the following: for i in range(date_col_search): if date_col_search[i] is True:...
The to_datetime function converts a date and time string from text to a DateTime object, not the other way round. So your format string must match the format of the date strings you are converting. See pandas.to_datetime — pandas 2.0.0...
When I use the value 45678 I get the following result: Python test result: 2095-01-23 00:00:00 [edit] I think I have found the problem. The following line tries to check if every column of the frame contains only numeric values: if...
Your issue might be related to the indexing of your 'gap_series DataFrame'. The '.tail(200)' method you are using is used to select the last 200 rows of your 'DataFrame', which might not be available for all coins at all times. This could result...
Is there a better way to shuffle the rows of a data frame and read them in chunks than what I currently have? What I have tried: This is my attempt: df = pd.read_csv("ExtractedData.csv") df_sampled = df.sample(frac=1)...
Parse each line, and convert the date information to a datetime — Basic date and time types — Python 3.8.5 documentation[^] Those should sort "properly" where strings sort by finding the first different character pair and basing the whole...
Hi there, I have the following Python Code, which is run in Jupyter Notebook :- import pandas as pd import requests from bs4 import BeautifulSoup import numpy as np import datetime as dt class work: def __init__(self,link): ...
I want to create 2 data frames out of the below list:- results = [ {'type': 'check_datatype', 'kwargs': {'table': 'cars', 'columns': ['car_id','index'], 'd_type': 'str'}, 'datasource_path': '/cars_dataset_ok/', ...
Hi there, I am using the following Line Of Code, in Pandas :- diff = df6.loc[~df6['Venue'].isin(df1['Venue'])] diff And I am not getting, the DataFrame Output result I want. I wan't to have the DataFrame Rows Showing, where any Rows in the...
I have made a pivot table for 4 columns. I have to plot the chart of that table.But at some places there is value NaN, which is making the plot to have gaps in between I want all the gaps to appear a line between the previous and forward point....
You already posted this question at Is there any function which can search for duplicate node based on specific attribute value and copy sub-elements/child elements to it?[^]. Please do not repost; if you have additional information then edit...
I'm trying to convert a Pandas DataFrame column from UNIX to Datetime, but I either get a mismatch error or the new dates are all 1970-01-01... I'm stuck for hours not knowing how to fix this... What I have tried: When I look at how my UNIX...
Complete newby here. I'm trying to parse a quite long simulation output with Python into a frame and write it into an excel sheet. I only want to parse certain entries, not the whole thing. (See my code below) The output I am trying to parse: ...
Main Table: Date_And_Time Date Time Tags Value A B C 2022-02-08 06:01 2022-02-08 06:01 A01.B04.C_01 1 A01 B04 C_01 2022-02-08 06:01 2022-02-08 06:01 A01.B04.C_02 2 A01 B04 C_02 2022-02-08...
Look at the documentation: pickle — Python object serialization — Python 3.10.2 documentation[^]. The load method requires a file object as the first parameter.
64 66 81 02 73 -column 1 64 96 34 81 22 - column 2 I have two columns with 5 elements. I want to transpose it. Expected Output : 64 66 81 02 73 - column 1 61 96 34 81 22 - column 2 What I have tried: I have tried transposing but...
Seems you want to use pandas.DataFrame.melt[^], which unpivot a DataFrame from wide to long format, optionally leaving identifiers set. Follow the link for examples.
it's a little bit complicated , i have this dataframe : ID TimeandDate Date Time 10 2020-08-07 07:40:09 2022-08-07 07:40:09 10 2020-08-07 08:50:00 2022-08-07 08:50:00 10 2020-08-07 12:40:09 2022-08-07 ...
I have a dataframe df ID ID2 escto1 escto2 escto3 1 A 1 0 0 2 B 0 1 0 3 C 0 0 3 4 D 0 2 0 so either using indexing or using wildcard like column name 'escto*' if df.iloc[:, 2:]>0 then df.helper=1 or df.loc[(df.iloc[:, 3:]>0,'Transfer')]=1...
Hello, I have a .txt that goes like this: USA Arizona - New Mexico Interstate 40 Interstate 10 South Dakota - Minneapolis Interstate 90 South Carolina - Washington Arizona - California ...
df = pd.DataFrame({'A': [1,4,4,3,7], 'B': [1,2,2,6,4], 'C ': range(10, 5, -1)}) A B C 1 1 10 4 2 9 4 2 8 3 6 7 7 4 6 This is my data frame with 5 rows and 3 columns. I have to find a way to drop rows by...
I am not 100% certain that this solves your problem, but it does what I think it is supposed to do: print(df) indexA, indexB = df.idxmax('index').values[:2] print(F"\n{indexA = }, {indexB = }") if indexA != indexB: df2 = df.drop(indexA)...
I have 2 dictionaries and a list which have information as: dic_merged={'A': [['K', 'J'], 2.0], 'B': [nan, nan], 'C': [['Y'], 1.0], 'D': [['B', 'C'], 2.0], 'J': [nan, nan], 'K': [nan, nan], 'G': [['A', 'H'], 2.0], 'Y': [['Z'], 1.0], 'H':...
I have this code working like this. i want this to ask for user input and put it inside pandas dataframe how many times do you want to input: 2 Input Name: First Input Age: 12 Input Name: Second Input Age: 32 ['First', 12, 'Second', 32] #this...
I'm programmatically trying to detect the column in a dataframe that contains dates & I'm converting the date values to the same format. My logic is to find the column name that contains the word 'Date' either as a whole word or as a sub-word...
I have a function that divides the values of a numeric column into the specified number of bins/categories, based on the ranges they fall into. These categories are numbered from 0 to the limit specified. And the column values are replaced with...
I don't do Python, but the error seems to be telling you that you're trying to iterate (for...) over something that is not a collection, but is a single object.
I wrote a function that converts all the dates of the specified date column to the specified format. Any missing or invalid date is replaced with a value specified by the user. The issue is, all the dates are being converted to the same default...
Because datetime objects don't have a format: they are stored as a number of ticks since a specified point in time and only display as any format when they are converted to a string for presentation to the user. Since you fill your column with...
Because neither of them are known, standard date formats. If you want to process those, you will have to detect the failure, and write your own code to do the conversion.
I gave you the answer in your previous post of this question at Transformation of "serial date" to the specified date format[^]. And as you can clearly see, items 12 and 14 are not valid dates so will always convert to NaT Once you have done the...
I have a dataset consisting of 'N' number of features/variables. One of these columns has missing values which I would like to interpolate. The interpolate() method of Pandas helps in doing so. The input for this method is the name of the column...
I want to experiment with different interpolation techniques. Some determining factors for choosing the appropriate interpolation techniques are: 1. Density of data (Checking if the data is dense or sparse) 2. Dimensionality of data (High...
Hey all I am new to python.i need your help to create a data frame. I need 5 columns(category,service,profile,os,price) in my data frame. The data is in nested form under every category(Com,DB) we have different services(ABC,XYZ) under every...
I wrote a function that converts all the dates of the specified date column to the specified format. Any missing or invalid date is replaced with a value specified by the user. The code also takes "serial dates" like "5679" into consideration....
I was coding a script that calculates percentage differnce of binance's close data and upbit's close data. import time import pandas as pd import pyupbit import ccxt import requests time.sleep(3) binanceX = ccxt.binance(config={ ...
I have data in dataframe in this following format: Row_1 AB123, 01-mar-2011, 30-mar-2011, data1, data2 Row_2 CD123, 01-mar-2011, 30-mar-2011, data1, data2 Row_3 CD123, 01-apr-2011, 30-apr-2011, data1, data2 Row_4 EF123,...
Hi I am working on an Amazon dataset which does not follow the traditional row and column format. Kindly advice on the best way to convert this into a easily manipulatable dataset in R. Thank you Dataset: ...
i am trying to send a data frame through socket. But I got some errors i try to remove them but can't. can anoyone help me What I have tried: i have tried this code import socket import pandas as pd import pickle df =...
df_4=pd.DataFrame() for i in range(100): if df_33[i]!=df_new[i]: print("not matching") else: dff=pd.concat([df_33,df_new]) print(dff) keyError:0 What I have tried: i was getting this error keyError:0
I wrote a program where a dataframe is traversed & when any column with the name 'Date' is encountered, all the rows under that column are supposed to be converted to a 'datetime' object using 'pd.to_datetime' in the format mentioned. But this...
I have a code that converts all the dates in the specified date column to the specified date format. In case the date is invalid or empty, it gets replaced by the replacement value specified. My code works as expected for all values except the...
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