seaborn not plotting scatterplot as expected - python-3.x
I have written the following simple code :
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
advertising = pd.read_csv("tv-marketing.csv")
sns.pairplot(advertising, x_vars=[
'TV'], y_vars='Sales', height=7, aspect=0.7)
The following is the .csv file that is being used here -
TV,Sales
230.1,22.1
44.5,10.4
17.2,9.3
151.5,18.5
180.8,12.9
8.7,7.2
57.5,11.8
120.2,13.2
8.6,4.8
199.8,10.6
66.1,8.6
214.7,17.4
23.8,9.2
97.5,9.7
204.1,19
195.4,22.4
67.8,12.5
281.4,24.4
69.2,11.3
147.3,14.6
218.4,18
237.4,12.5
13.2,5.6
228.3,15.5
62.3,9.7
262.9,12
142.9,15
240.1,15.9
248.8,18.9
70.6,10.5
292.9,21.4
112.9,11.9
97.2,9.6
265.6,17.4
95.7,9.5
290.7,12.8
266.9,25.4
74.7,14.7
43.1,10.1
228,21.5
202.5,16.6
177,17.1
293.6,20.7
206.9,12.9
25.1,8.5
175.1,14.9
89.7,10.6
239.9,23.2
227.2,14.8
66.9,9.7
199.8,11.4
100.4,10.7
216.4,22.6
182.6,21.2
262.7,20.2
198.9,23.7
7.3,5.5
136.2,13.2
210.8,23.8
210.7,18.4
53.5,8.1
261.3,24.2
239.3,15.7
102.7,14
131.1,18
69,9.3
31.5,9.5
139.3,13.4
237.4,18.9
216.8,22.3
199.1,18.3
109.8,12.4
26.8,8.8
129.4,11
213.4,17
16.9,8.7
27.5,6.9
120.5,14.2
5.4,5.3
116,11
76.4,11.8
239.8,12.3
75.3,11.3
68.4,13.6
213.5,21.7
193.2,15.2
76.3,12
110.7,16
88.3,12.9
109.8,16.7
134.3,11.2
28.6,7.3
217.7,19.4
250.9,22.2
107.4,11.5
163.3,16.9
197.6,11.7
184.9,15.5
289.7,25.4
135.2,17.2
222.4,11.7
296.4,23.8
280.2,14.8
187.9,14.7
238.2,20.7
137.9,19.2
25,7.2
90.4,8.7
13.1,5.3
255.4,19.8
225.8,13.4
241.7,21.8
175.7,14.1
209.6,15.9
78.2,14.6
75.1,12.6
139.2,12.2
76.4,9.4
125.7,15.9
19.4,6.6
141.3,15.5
18.8,7
224,11.6
123.1,15.2
229.5,19.7
87.2,10.6
7.8,6.6
80.2,8.8
220.3,24.7
59.6,9.7
0.7,1.6
265.2,12.7
8.4,5.7
219.8,19.6
36.9,10.8
48.3,11.6
25.6,9.5
273.7,20.8
43,9.6
184.9,20.7
73.4,10.9
193.7,19.2
220.5,20.1
104.6,10.4
96.2,11.4
140.3,10.3
240.1,13.2
243.2,25.4
38,10.9
44.7,10.1
280.7,16.1
121,11.6
197.6,16.6
171.3,19
187.8,15.6
4.1,3.2
93.9,15.3
149.8,10.1
11.7,7.3
131.7,12.9
172.5,14.4
85.7,13.3
188.4,14.9
163.5,18
117.2,11.9
234.5,11.9
17.9,8
206.8,12.2
215.4,17.1
284.3,15
50,8.4
164.5,14.5
19.6,7.6
168.4,11.7
222.4,11.5
276.9,27
248.4,20.2
170.2,11.7
276.7,11.8
165.6,12.6
156.6,10.5
218.5,12.2
56.2,8.7
287.6,26.2
253.8,17.6
205,22.6
139.5,10.3
191.1,17.3
286,15.9
18.7,6.7
39.5,10.8
75.5,9.9
17.2,5.9
166.8,19.6
149.7,17.3
38.2,7.6
94.2,9.7
177,12.8
283.6,25.5
232.1,13.4
This is the output graph that I am getting (Running it from vscode->Run Current File
in Interactive Window
vscode output
But the expected output form the example that I took should be like this :
expected output 1
expected output 2
**Neither do I see the scatterplot, also the scaling is different.**
I believe the code you are looking for is the following:
sns.scatterplot(x='TV', y='Sales', data=advertising)
If you want to use pairplot then you can use:
sns.pairplot(advertising, height=7, aspect=0.7)
or:
sns.pairplot(sample_data, x_vars=['TV'], y_vars=['Sales'], height=7, aspect=0.7, kind='scatter', diag_kind=None)
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enter image description herejust got wrong figure[enter image
description here][2], using python 3.7.
import matplotlib.pyplot as plt
import pandas as pd
data = pd.read_csv('data.txt', header=-1)
data.columns =['A']
data.hist('A', bins=20, density=True)
plt.show()
A Question with using scapy.sniff for get the 'Ethernet Frame' in pcap files
Aim: Get the arrival time from the pcap files
Language: python3.7
Tools: Scapy.sniff
Above all ,i want get the arrival time data,in the .pcap ,when i use wireshark ,i saw the data in the Ethernet Frame,but when i use
#Scapy.sniff(offline='.pcap') ,i just get the Ether,TCP,IP and others ,so how can i get that data?
Thanx alot!
>>from scapy.all import *
>>a = sniff(offline = '***.pcap')
>>a[0]
[out]:
<Ether dst=*:*:*:*:*:* src=*:*:*:*:*:* type=** |<IP version=4 ihl=5 tos=0x20 len=52 id=14144 flags=DF frag=0 ttl=109 proto=tcp chksum=0x5e3b src=*.*.*.* dst=*.*.*.* |<TCP sport=gcsp dport=http seq=1619409885 ack=1905830025 dataofs=8 reserved=0 flags=A window=65535 chksum=0xfdb5 urgptr=0 options=[('NOP', None), ('NOP', None), ('SAck', (1905831477, 1905831485))] |>>>
[ ]:
The packet time from the pcap is available in the time member: print(a[0].time) It's kept as a floating point value (the standard python "timestamp" format). To get it in a form more easily understandable, you may want to use the datetime module: >>> from datetime import datetime >>> dt = datetime.fromtimestamp(a[0].time) >>> print(dt) 2018-11-12 03:03:00.259780 The scapy documentation isn't great. It can be very instructive to use the interactive help facility. For example, in the interpreter: $ python >>> from scapy.all import * >>> a = sniff(offline='mypcap.pcap') >>> help(a[0]) This will show you all the methods and attributes of the object represented by a[0]. In your case, that is an instance of class Ether(scapy.packet.Packet).
how to perform calculation for all elements of list parellely or simultaneously to reduce the run time?
I am extracting a dataframe from yahoo API for a list of companies but I want to do it paralelly(i.e, the dataframes for all the companies should be extracted simultaneously).So, it reduces my run time....
My code:
import pandas_datareader.data as web
import pandas as pd
import datetime
end_date = datetime.datetime.now().strftime('%d/%m/%Y')
temp = datetime.datetime.now() - datetime.timedelta(6*365/12)
start_date = temp.strftime('%d/%m/%Y')
f = web.DataReader('ACC.NS', 'yahoo', start_date, end_date)
print(f)
The output of this code is a dataframe shown below:
This i have done for single company....
I want to do it for a list of companies which is:
Company_Names = ['ACC', 'ADANIENT', 'ADANIPORTS', 'ADANIPOWER', 'AJANTPHARM', 'ALBK', 'AMARAJABAT', 'AMBUJACEM', 'APOLLOHOSP', 'APOLLOTYRE', 'ARVIND', 'ASHOKLEY', 'ASIANPAINT', 'AUROPHARMA', 'AXISBANK',
'BAJAJ-AUTO', 'BAJFINANCE', 'BAJAJFINSV', 'BALKRISIND', 'BANKBARODA', 'BANKINDIA', 'BATAINDIA', 'BEML', 'BERGEPAINT', 'BEL', 'BHARATFIN', 'BHARATFORG', 'BPCL', 'BHARTIARTL', 'INFRATEL', 'BHEL', 'BIOCON', 'BOSCHLTD', 'BRITANNIA',
'CADILAHC', 'CANFINHOME', 'CANBK', 'CAPF', 'CASTROLIND', 'CEATLTD', 'CENTURYTEX', 'CESC', 'CGPOWER', 'CHENNPETRO', 'CHOLAFIN', 'CIPLA', 'COALINDIA', 'COLPAL', 'CONCOR', 'CUMMINSIND', 'DABUR', 'DCBBANK',
'DHFL', 'DISHTV', 'DIVISLAB', 'DLF', 'DRREDDY', 'EICHERMOT', 'ENGINERSIN', 'EQUITAS', 'ESCORTS', 'EXIDEIND',
'FEDERALBNK', 'GAIL', 'GLENMARK', 'GMRINFRA', 'GODFRYPHLP', 'GODREJCP', 'GODREJIND', 'GRANULES', 'GRASIM', 'GSFC', 'HAVELLS', 'HCLTECH', 'HDFCBANK', 'HDFC', 'HEROMOTOCO', 'HEXAWARE', 'HINDALCO', 'HCC', 'HINDPETRO', 'HINDUNILVR',
'HINDZINC', 'ICICIBANK', 'ICICIPRULI', 'IDBI', 'IDEA', 'IDFCBANK', 'IDFC', 'IFCI', 'IBULHSGFIN', 'INDIANB', 'IOC', 'IGL', 'INDUSINDBK', 'INFIBEAM', 'INFY', 'INDIGO', 'IRB', 'ITC', 'JISLJALEQS', 'JPASSOCIAT', 'JETAIRWAYS', 'JINDALSTEL',
'JSWSTEEL', 'JUBLFOOD', 'JUSTDIAL', 'KAJARIACER', 'KTKBANK', 'KSCL', 'KOTAKBANK', 'KPIT', 'L&TFH', 'LT', 'LICHSGFIN', 'LUPIN', 'M&MFIN', 'MGL', 'M&M', 'MANAPPURAM', 'MRPL', 'MARICO', 'MARUTI', 'MFSL', 'MINDTREE', 'MOTHERSUMI', 'MRF', 'MCX',
'MUTHOOTFIN', 'NATIONALUM', 'NBCC', 'NCC', 'NESTLEIND', 'NHPC', 'NIITTECH', 'NMDC', 'NTPC', 'ONGC', 'OIL', 'OFSS', 'ORIENTBANK', 'PAGEIND', 'PCJEWELLER', 'PETRONET', 'PIDILITIND', 'PEL', 'PFC', 'POWERGRID', 'PTC', 'PNB', 'PVR', 'RAYMOND',
'RBLBANK', 'RELCAPITAL', 'RCOM', 'RELIANCE', 'RELINFRA', 'RPOWER', 'REPCOHOME', 'RECLTD', 'SHREECEM', 'SRTRANSFIN', 'SIEMENS', 'SREINFRA', 'SRF', 'SBIN', 'SAIL', 'STAR', 'SUNPHARMA', 'SUNTV', 'SUZLON', 'SYNDIBANK', 'TATACHEM', 'TATACOMM', 'TCS',
'TATAELXSI', 'TATAGLOBAL', 'TATAMTRDVR', 'TATAMOTORS', 'TATAPOWER', 'TATASTEEL', 'TECHM', 'INDIACEM', 'RAMCOCEM', 'SOUTHBANK', 'TITAN', 'TORNTPHARM', 'TORNTPOWER', 'TV18BRDCST', 'TVSMOTOR', 'UJJIVAN', 'ULTRACEMCO', 'UNIONBANK', 'UBL', 'UPL',
'VEDL', 'VGUARD', 'VOLTAS', 'WIPRO', 'WOCKPHARMA', 'YESBANK', 'ZEEL']
For all this companies the dataframe 'f' should be extracted parallely in order to save run time. Can anyone help me to solve this?