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iteritems() DateFrame output mechanics and append() output into a new DataFrame


iteritems() DateFrame output mechanics and append() output into a new DataFrame

By : user2185323
Date : November 21 2020, 04:01 AM
will help you pandas.iteritems iterates over pairs of the form name, column (series to be more precise), you can check that by looking at this example
code :
for value in test.iteritems():
    print(value[0])
Beer
Whiskey
returns = 100 * test.diff(5) / test.shift(5)
print(returns)
                Beer   Whiskey
Date                          
1978-12-29       NaN       NaN
1979-01-02       NaN       NaN
1979-01-03       NaN       NaN
1979-01-04       NaN       NaN
1979-01-05       NaN       NaN
1979-01-08 -1.283186  0.820809
1979-01-09 -1.234568  1.259824
1979-01-10  0.960659  0.263128
1979-01-11 -1.120072  0.662554
1979-01-12 -3.503326  0.628643


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Convert byte to binary, append output to string, convert to double, print output...losing bits on output

Convert byte to binary, append output to string, convert to double, print output...losing bits on output


By : Tharindra Kaumudi Wi
Date : March 29 2020, 07:55 AM
should help you out So, I am having trouble with some code. , First:
code :
strcat(str, binary);
 char binary[100];
binary[size] = '\0';
Windows command processor: Output redirection mechanics

Windows command processor: Output redirection mechanics


By : Geophysicist
Date : March 29 2020, 07:55 AM
will be helpful for those in need Based off a Process Monitor trace, when echo text > filename.txt is ran, a call is made to CreateFile with the dwCreationDisposition flag set to CREATE_ALWAYS, which
Unexpected output replacing words using dictionary and dic.iteritems - Python

Unexpected output replacing words using dictionary and dic.iteritems - Python


By : user2315383
Date : March 29 2020, 07:55 AM
this will help Use an OrderedDict so that the replacements occur in the order you expect.
code :
from collections import OrderedDict

dicnames = OrderedDict([
    ('svcs', 'services'),
    ('hlth', 'health'),
    ('equip', 'equipment'),
    ('corp', 'corporation'),
    ('intl', 'international'),
    ('co', 'company'),
])

def reemp(text):
    for i , j in dicnames.iteritems():
        text = text.replace(i,j)
    return text

print(reemp('uni corp'))
def reemp(text):
    for i , j in dicnames.iteritems():
        if i in text:
            return text.replace(i,j)
    return text
Append results of DataFrame apply lamda to DateFrame or new Series

Append results of DataFrame apply lamda to DateFrame or new Series


By : Richard
Date : March 29 2020, 07:55 AM
may help you . It appears you need to use pd.Series.apply(pd.Series).
Here is a minimal example:
code :
import pandas as pd

df = pd.DataFrame({0: [1, 2, 3, 4]})

def add_some(row):
    return row[0]+1, row[0]+2, row[0]+3

df[[1, 2, 3]] = df.apply(add_some, axis=1).apply(pd.Series)

print(df)

   0  1  2  3
0  1  2  3  4
1  2  3  4  5
2  3  4  5  6
3  4  5  6  7
How to i append the output from beautifulsoup to a pandas dataframe

How to i append the output from beautifulsoup to a pandas dataframe


By : eduardogarcia234
Date : March 29 2020, 07:55 AM
seems to work fine You're not extracting the href attributes from the tags you are pulling. What you want to do is find all tags with links (which you did, but you need to use find_all as find will just return the first 1 it finds.) Then iterate through those tags. I choose to just have it look for the substring 'Year' and if it does, put that into the list.
code :
#import packages
import numpy as np
import pandas as pd
from bs4 import BeautifulSoup
import requests

#start of code
mainurl = "https://aviation-safety.net/database/"
def getAndParseURL(mainurl):
   result = requests.get(mainurl)
   soup = BeautifulSoup(result.content, 'html.parser')
   datatable = soup.find_all('a', href = True)
   return datatable

datatable = getAndParseURL(mainurl)

#go through the content and grab the URLs
links = []
for link in datatable:
    if 'Year' in link['href']:
        url = link['href']
        links.append(mainurl + url)


#check if links are in dataframe
df = pd.DataFrame(links, columns=['url'])

df.head(10)
df.head(10)
Out[24]: 
                                                 url
0  https://aviation-safety.net/database/dblist.ph...
1  https://aviation-safety.net/database/dblist.ph...
2  https://aviation-safety.net/database/dblist.ph...
3  https://aviation-safety.net/database/dblist.ph...
4  https://aviation-safety.net/database/dblist.ph...
5  https://aviation-safety.net/database/dblist.ph...
6  https://aviation-safety.net/database/dblist.ph...
7  https://aviation-safety.net/database/dblist.ph...
8  https://aviation-safety.net/database/dblist.ph...
9  https://aviation-safety.net/database/dblist.ph...
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