pandas

问题 I have a Dataframe that looks like below data = [(datetime.datetime(2021, 2, 10, 7, 49, 7, 118658), u'12.100.90.10', u'100.100.12.1', u'LT_DOWN'), (datetime.datetime(2021, 2, 10, 7, 49, 14, 312273), u'12.100.90.10', u'100.100.12.1', u'LT_UP'), (datetime.datetime(2021, 2, 10, 7, 49, 21, 535932), u'12.100.90.10', u'100.100.12.1', u'LT_UP'), (datetime.datetime(2021, 2, 10, 7, 50, 28, 725961), u'12.100.90.10', u'100.100.12.1', u'PL_DOWN'), (datetime.datetime(2021, 2, 10, 7, 50, 32, 450853), u'10

问题 This question already has answers here : how to highlight weekends for time series line plot in python (2 answers) Closed 3 days ago . i plotted a daily line plot for flights and i would like to highlight all the saturdays and sundays. I'm trying to do it with axvspan but i'm struggling with the use of it? Any suggestions on how can this be coded? (flights.loc[flights['date'].dt.month.between(1, 2), 'date'] .dt.to_period('D') .value_counts() .sort_index() .plot(kind="line",figsize=(12,6)) )

问题 In dataframe I need to delete some cells and shift left others in row : df=pd.DataFrame({'X0':['anytext','anytext','anytext','anytext','anytext'], 'X1':['12:40','boss','engen','15:44','16:01'], 'X2':['anytext','12:44','14:06','anytext','anytext'], 'X3':['anytext','anytext','anytext','anytext','anytext']}) df X0 X1 X2 X3 0 anytext 12:40 anytext anytext 1 anytext boss 12:44 anytext 2 anytext engen 14:06 anytext 3 anytext 15:44 anytext anytext 4 anytext 16:01 anytext anytext I want to delete

问题 In dataframe I need to delete some cells and shift left others in row : df=pd.DataFrame({'X0':['anytext','anytext','anytext','anytext','anytext'], 'X1':['12:40','boss','engen','15:44','16:01'], 'X2':['anytext','12:44','14:06','anytext','anytext'], 'X3':['anytext','anytext','anytext','anytext','anytext']}) df X0 X1 X2 X3 0 anytext 12:40 anytext anytext 1 anytext boss 12:44 anytext 2 anytext engen 14:06 anytext 3 anytext 15:44 anytext anytext 4 anytext 16:01 anytext anytext I want to delete

问题 So I have the following code which reads in 5 columns, date ohlc. It then creates a column 'dow' to hold day of week. So far so good: import numpy as np import pandas as pd df = pd.read_csv('/content/drive/MyDrive/Forex/EURUSD-2018_12_18-2020_11_01.csv',parse_dates=True,names = ['date','1','2','3','4',]) df['date'] = pd.to_datetime(df['date']) df.index = df['date'] df['dow'] = df['date'].dt.dayofweek #df['downum'] = df.apply(lambda x: downu(x['date'])) df Producing the following output: date

问题 Recently, I asked the following question - Unwanted white spaces resulting into distorted column and the answer by @sharathnatraj was satisfactory and worked like a charm. Answer was: import re with open('trial1.txt', 'r') as f: lines = f.readlines() l = [re.sub(r"([a-z]{5,})\s([a-z]{5,})", r"\1\2", line) for line in lines] df = pd.read_csv(io.StringIO('\n'.join(l)), delim_whitespace=True) Sample data set: 1 CAgF3O3S silver trifluoromethanesulfonate 2923-28-6 256.937 629.15 1 --- --- --- ---

问题 Recently, I asked the following question - Unwanted white spaces resulting into distorted column and the answer by @sharathnatraj was satisfactory and worked like a charm. Answer was: import re with open('trial1.txt', 'r') as f: lines = f.readlines() l = [re.sub(r"([a-z]{5,})\s([a-z]{5,})", r"\1\2", line) for line in lines] df = pd.read_csv(io.StringIO('\n'.join(l)), delim_whitespace=True) Sample data set: 1 CAgF3O3S silver trifluoromethanesulfonate 2923-28-6 256.937 629.15 1 --- --- --- ---

问题 I'm working on a Sentiment Analysis project using the Google Cloud Natural Language API and Python, this question might be similar to this other question, what I'm doing is the following: Reads a CSV file from Google Cloud Storage, file has approximately 7000 records. Converts the CSV into a Pandas DataFrame. Iterates over the dataframe and calls the Natural Language API to perform sentiment analysis on one of the dataframe's columns, on the same for loop I extract the score and magnitude

问题 I'm trying to calculate the percentage of each crime of the following Dataframe: Violent Murder Larceny_Theft Vehicle_Theft Year 1960 288460 3095700 1855400 328200 1961 289390 3198600 1913000 336000 1962 301510 3450700 2089600 366800 1963 316970 3792500 2297800 408300 1964 364220 4200400 2514400 472800 So I should calculate first the total of crimes per year and then use that to calculate the percentage of each crime. I was trying the following: > perc = (crime *100) / crime.sum(axis=1) Any

问题 I'm trying to calculate the percentage of each crime of the following Dataframe: Violent Murder Larceny_Theft Vehicle_Theft Year 1960 288460 3095700 1855400 328200 1961 289390 3198600 1913000 336000 1962 301510 3450700 2089600 366800 1963 316970 3792500 2297800 408300 1964 364220 4200400 2514400 472800 So I should calculate first the total of crimes per year and then use that to calculate the percentage of each crime. I was trying the following: > perc = (crime *100) / crime.sum(axis=1) Any