import pandas as pd
import numpy as np
#load data
#data file and py file must be in same file path
df = pd.read_csv('cbp15st.txt', delimiter = ',', encoding = 'utf-8-
sig')
#define load data DataFrame columns
state = df['FIPSTATE']
industry = df['NAICS']
legal_form_of_organization = df['LFO']
suppression_flag = df['EMPFLAG']
total_establishment = df['EST']
establishment_1_4 = df['N1_4']
establishment_5_9 = df['N5_9']
establishment_10_19 = df['N10_19']
establishment_20_49 = df['N20_49']
establishment_50_99 = df['N50_99']
establishment_100_249 = df['N100_249']
establishment_250_499 = df['N250_499']
establishment_500_999 = df['N500_999']
establishment_1000_more = df['N1000']
#use df.loc to parse dataset for partiuclar value types
print(df.loc[df['EMPFLAG']=='A'], df.loc[df['FIPSTATE']==1],
df.loc[df['NAICS']=='------'])
Currently using df.loc to locate specific values from the df columns, but will read out those columns that contain all of these values, not only these values (like an or vs and statement)
Trying to find a way to place multiple restrictions on this to only get column reads that meet criteria x y and z.
Current Readout from above:
enter image description here
You can use & operator while specifying multiple filtering criteria, something like:
df1 = df.loc[(df['EMPFLAG']=='A']) & (df['FIPSTATE']==1) & (df['NAICS']=='------')]
print(df1)
Related
I am relatively new with python - and I am struggling to do the following:
I have a set of different data frames, with sequential naming (df_i), which I want to access in a for loop based on their name (with an string), how can I do that? e.g.
df_1 = pd.read_csv('...')
df_2 = pd.read_csv('...')
df_3 = pd.read_csv('...')
....
n_df = 3
for i in range(len(n_df)):
df_namestr= 'df_' + str(i+1)
# ---------------------
df_temp = df_namestr
# ---------------------
# Operate with df_temp. For i+1= 1, df_temp should be df_1
Kind regards,
DF
You can try something like that:
for n in range(1, n_df+1):
df_namestr = f"df_{n}"
df_tmp = locals().get(df_namestr)
if not isinstance(df_tmp, pd.DataFrame):
continue
print(df_namestr)
print(df_tmp)
Refer to the documentation of locals() to know more.
Would it be better to approach the accessing of multiple dataframes by reading them into a list?
You could put all the csv files required in a subfolder and read them all in. Then they are in a list and you can access each one as an item in that list.
Example:
import pandas as pd
import glob
path = r'/Users/myUsername/Documents/subFolder'
csv_files = glob.glob(path + "/*.csv")
dfs = []
for filename in csv_files:
df = pd.read_csv(filename)
dfs.append(df)
print(len(dfs))
print(dfs[1].head())
Need some help appending several webscraping resaults to a panda df.
Currently im only getting the output from one of the URLs to the DF.
I left out the URLs, if you need them i will supply them to you.
##libs
import bs4
import requests
import re
from time import sleep
import pandas as pd
from bs4 import BeautifulSoup as bs
##webscraping targets
URLs = ["URL1","URL2","URL3"]
## Get columns
column_list = []
r1 = requests.get(URLs[0])
soup1 = bs(r1.content)
data1 = soup1.find_all('dl', attrs= {"class": "border XSText rightAlignText noMarginTop highlightOnHover thickBorderBottom noTopBorder"})
columns = soup1.find_all('dt')
for col in columns:
column_list.append(col.text.strip()) # strip() removes extra space from the text
##Get values
value_list = []
for url in URLs:
r1 = requests.get(url)
soup1 = bs(r1.content)
data1 = soup1.find_all('dl', attrs= {"class": "border XSText rightAlignText noMarginTop highlightOnHover thickBorderBottom noTopBorder"})
values = soup1.find_all('dd')
for val in values:
value_list.append(val.text.strip())
df=pd.DataFrame(list(zip(column_list,value_list)))
df.transpose()
Current output only showing the resaults of one URL:
Expected output:
The problem here is with your zip function. It will only zip the values until the length of the shortest list, in this case, the column_list. Leaving all the other values unused.
If you want to append the other values to the dataframe as well you will have to iterate over then. So change the last two lines on your code to this and it should work:
result = [[i] for i in column_list]
for i, a in enumerate(value_list):
result[i % len(column_list)].extend([a])
df = pd.DataFrame(result)
df.transpose()
i need to know what is happening in my code? it should give data in separate columns it is giving me same data in a oath columns.
i tried to change the value of row variable but it didn't found the reason
import requests
import csv
from bs4 import BeautifulSoup
import pandas as pd
import time
arrayofRequest= []
prices=[]
location=[]
columns=['Price', 'Location']
df = pd.DataFrame(columns=columns)
for i in range(0,50):
arrayofRequest.append("https://www.zameen.com/Homes/Karachi-2-"+str(i+1)+".html?gclid=Cj0KCQjw3JXtBRC8ARIsAEBHg4mj4jX1zZUt3WzGScjH6nfwzrEqkuILarcmg372imSneelSXPj0fGIaArNeEALw_wcB")
request = requests.get(arrayofRequest[i])
soupobj= BeautifulSoup(request.content,"lxml")
# print(soupobj.prettify())
links =soupobj.find_all('span',{'class':'f343d9ce'})
addresses =soupobj.find_all('div',{'class':'_162e6469'})
price = ""
for i in range(0,len(links)):
price = str(links[i]).split(">")
price = price[len(price)-2].split("<")[0]
prices.append(price)
address = str(addresses[i]).split(">")
address = address[len(address)-2].split("<")[0]
location.append(address)
row=location[i]+","+prices[i]
df = df.append(pd.Series(row, index=columns), ignore_index=False)
# filewriter = csv.writer(csvfile, delimiter=',',filewriter.writerow(['Price', 'Location']),filewriter.writerow([prices[0],location[0]])
df.to_csv('DATA.csv', index=False)
because of this:
pd.Series(row, index=columns)
try smthg like
pd.DataFrame([[locations[i], prices[i]]], index=columns))
However this could be done only once outside of your for loop
pd.DataFrame(list(zip(locations, prices)), index=columns))
In the below code, the dataframe df5 is not getting populated. I am just assigning the values to dataframe's columns and I have specified the column beforehand. When I print the dataframe, it returns an empty dataframe. Not sure whether I am missing something.
Any help would be appreciated.
import math
import pandas as pd
columns = ['ClosestLat','ClosestLong']
df5 = pd.DataFrame(columns=columns)
def distance(pt1, pt2):
return math.sqrt((pt1[0] - pt2[0])**2 + (pt1[1] - pt2[1])**2)
for pt1 in df1:
closestPoints = [pt1, df2[0]]
for pt2 in df2:
if distance(pt1, pt2) < distance(closestPoints[0], closestPoints[1]):
closestPoints = [pt1, pt2]
df5['ClosestLat'] = closestPoints[1][0]
df5['ClosestLat'] = closestPoints[1][0]
df5['ClosestLong'] = closestPoints[1][1]
print ("Point: " + str(closestPoints[0]) + " is closest to " + str(closestPoints[1]))
From the look of your code, you're trying to populate df5 with a list of latitudes and longitudes. However, you're making a couple mistakes.
The columns of pandas dataframes are Series, and hold some type of sequential data. So df5['ClosestLat'] = closestPoints[1][0] attempts to assign the entire column a single numerical value, and results in an empty column.
Even if the dataframe wasn't ignoring your attempts to assign a real number to the column, you would lose data because you are overwriting the column with each loop.
The Solution: Build a list of lats and longs, then insert into the dataframe.
import math
import pandas as pd
columns = ['ClosestLat','ClosestLong']
df5 = pd.DataFrame(columns=columns)
def distance(pt1, pt2):
return math.sqrt((pt1[0] - pt2[0])**2 + (pt1[1] - pt2[1])**2)
lats, lngs = [], []
for pt1 in df1:
closestPoints = [pt1, df2[0]]
for pt2 in df2:
if distance(pt1, pt2) < distance(closestPoints[0], closestPoints[1]):
closestPoints = [pt1, pt2]
lats.append(closestPoints[1][0])
lngs.append(closestPoints[1][1])
df['ClosestLat'] = pd.Series(lats)
df['ClosestLong'] = pd.Series(lngs)
I am trying to get the data from the list (list_addresses) and populate it to different columns of the dataframe (dfloc). I use the below code, not sure where I am going wrong.
Values are present in list_addresses but not getting populated to the dataframe.
Any help would be appreciated.
for index in range(len(list_addresses)):
location = geolocator.reverse([list_addresses[index][0],list_addresses[index][1]])
dfloc.loc[dfloc.Latitude] = list_addresses[index][0]
dfloc.loc[dfloc.Longitude] = list_addresses[index][1]
dfloc.loc[dfloc.Address] = location.address
So it looks like you have a list of lists or tuples with form of [(Lat1,Lon1),(Lat2,Lon2), etc...]. I like to make a list for each column, then assign the entire column at once:
lat_list = [x[0] for x in list_addresses]
lon_list = [x[1] for x in list_addresses]
address_list = []
for index in range(len(list_addresses)):
location = geolocator.reverse([list_addresses[index][0],list_addresses[index][1]])
address_list.append(location.address)
dfloc['Latitude'] = lat_list
dfloc['Longitude'] = lon_list
dfloc['Address'] = address_list