I'm a beginner who try to make followers network of twitter with Python3. I made this code and got result however always one node is separated as you can see like left bottom node.
I have no idea what is happening. In addition, I also want to see smaller world for instance, how can I pick up only 5 friends and elucidate their connection ?? This my result is too huge... It would be greatly appreciated if you could explain the details. Here is my code :
api = twitter.Api(consumer_key = my_consumer_key,
consumer_secret = my_consumer_secret,
access_token_key = my_access_token_key,
access_token_secret = my_access_token_secret,
input_encoding = "UTF-8",
sleep_on_rate_limit=True)
friends = api.GetFriends()
G = networkx.Graph()
for friend in friends:
G.add_edge(myname,friend.screen_name)
for friend in friends[-3:]:
for user in api.GetFriends(friend.id):
if user in friends:
G.add_edge(friend.screen_name,user.screen_name)
pos = spring_layout(G)
draw_networkx_nodes(G, pos, node_size = 100, node_color = 'w')
draw_networkx_edges(G, pos, width = 1)
draw_networkx_labels(G, pos, font_size = 12, font_family = 'sans-
serif', font_color = 'r')
xticks([])
yticks([])
savefig("egonetwork.png")
show()
Related
I'm re-posting this question since I didn't make a good example code in last question.
I'm trying to make a nodes to set in specific location.
But I found out that the output drawing is not... fixed. Let me show you the pic.
So this is the one I make with 10 nodes. worked perfectly as I intended.
Also it has plt.text on the bottom left.
And here's the other picture
As you can see, something is wrong. plt.text is gone, and USA's location is weird. Actually that location is where DEU is located in the first pic. Both pics use same code.
Now, let me show you some of my code.
for spec_df, please download from my gdrive:
https://drive.google.com/drive/folders/11X_i5-pRLGBfQ9vIwQ3hfDU5EWIfR3Uo?usp=sharing
auto_flag = 0
spec_df=pd.read_stata("C:\\"Your_file_loc"\\CombinedHS6_example.dta")
#top_10_list = ["USA","CHN","KOR"] (Try for three nodes)
#or
#auto_flag = 1 (Try for 10 nodes)
df_p = spec_df[['partneriso3','tradevalue']]
df_p = df_p.groupby('partneriso3').sum().reset_index()
df_r = spec_df[['reporteriso3','tradevalue']]
df_r = df_r.groupby('reporteriso3').sum().reset_index()
df_r = df_r.rename(columns={'reporteriso3': 'Nation'})
df_r = df_r.rename(columns={'tradevalue': 'tradevalue_r'})
df_p = df_p.rename(columns={'partneriso3': 'Nation'})
df_s = pd.merge(df_r, df_p, on='Nation', how='outer').fillna(0)
df_s["final"] = df_s['tradevalue'] + df_s['tradevalue_r']
if auto_flag == 1:
df_s = df_s.sort_values(by=['final'], ascending = False).reset_index()
cut = df_s[:10]
else:
cut = df_s[(df_s['Nation'].isin(top_10_list))]
cut['final'] = cut['final'].apply(lambda x: normalize(x, cut['final'].max()))
cut['font_size'] = cut['final'] * 13
cut['final'] = cut['final'] * 1500
top_10_list = list(cut["Nation"])
top10 = spec_df[(spec_df['reporteriso3'].isin(top_10_list))&(spec_df['partneriso3'].isin(top_10_list))]
top10['tradevalue'] = top10['tradevalue'].apply(lambda x: normalize(x, top10['tradevalue'].max()))
top10['tradevalue'] = top10['tradevalue']*10
plt.figure(figsize=(10,10), dpi = 100)
G = nx.from_pandas_edgelist(top10, 'reporteriso3', 'partneriso3', 'tradevalue', create_using= nx.DiGraph())
widths = nx.get_edge_attributes(G,'tradevalue')
pos = {}
pos_cord = [(-0.30779309, -0.26419882), (0.26767895, 0.19524759), (-0.38479095, 0.88179998), (0.33785317, 0.96090914), (0.94090464, 0.40707934), (0.9270665, -0.38403114), (0.41246223, -0.85684049), (-0.32083322, -1.0), (-0.99724456, -0.34947554), (-0.87530367, 0.40950993)]
for t in range(len(top_10_list)):
if top_10_list == "":
continue
else:
pos[top_10_list[t]] = pos_cord[t]
pos_nodes = nudge(pos, 0, 0.12)
nx.draw_networkx_edges(G,pos, width=list(widths.values()), edge_color = '#9ECAE4')
nx.draw_networkx_nodes(G, pos=pos, nodelist = cut['Nation'], node_size= cut['final'], node_color ='#AB89EF', edgecolors ='#000000')
nx.draw_networkx_labels(G,pos_nodes, font_size=15)
plt.text(-1.15,-1.15,s='hs : ')
plt.savefig(location,dpi=300)
Sorry for the crude code. But I want to ask that I'm using fixed coordinates. So nodes are not supposed to move there location. So I think the plt's size is kinda interacting with the contents...? But I don't know how it does that.
Could anyone enlighten me please? This drives me crazy...
Thanks to #Paul Brodersen's comment, I found a way to fix the location.
I just added these codes in my codes.
fig = plt.figure(figsize=(10,10), dpi = 100)
axes = fig.add_axes([0,0,1,1])
axes.set_xlim([-1.3,1.3])
axes.set_ylim([-1.3,1.3])
Thank you for the help again!
I am having some issues with some code. I have set about a project for creating Bitcoin wallets in an attempt to turn a hobby into a learning experience, whereby I can understand both Python and the Bitcoin protocol in more detail. I have posted here rather than in the Bitcoin site as the question is related to Python programming.
Below I have some code which I have created to turn a private key into a WIF key. I have written this out for clarity rather than the most optimal method of coding, so that I can see all the steps clearly and work on issues. This code was previously a series lines which I have now progressed into a class with functions.
I am following the example from this page: https://en.bitcoin.it/wiki/Wallet_import_format
Here is my current code:
import hashlib
import codecs
class wif():
def private_to_wif(private_key):
extended_key = wif.create_extended(private_key)
address = wif.create_wif_address(extended_key)
return address
def create_extended(private_key):
private_key1 = bytes.fromhex(private_key)
private_key2 = codecs.encode(private_key1, 'hex')
mainnet = b'80'
#testnet = b'ef'
#compressed = b'01'
extended_key = mainnet + private_key2
return extended_key
def create_wif_address(extended_key):
first_hash = hashlib.sha256(extended_key)
first_digest = first_hash.digest()
second_hash = hashlib.sha256(first_digest)
second_digest = second_hash.digest()
second_digest_hex = codecs.encode(second_digest, 'hex')
checksum = second_digest_hex[:8]
extended_key_chksm = (extended_key + checksum).decode('utf-8')
wif_address = base58(extended_key_chksm)
return wif_address
def base58(extended_key_chksm):
alphabet = '123456789ABCDEFGHJKLMNPQRSTUVWXYZabcdefghijkmnopqrstuvwxyz'
b58_string = ''
leading_zeros = len(extended_key_chksm) - len(extended_key_chksm.lstrip('0'))
address_int = int(extended_key_chksm, 16)
while address_int > 0:
digit = address_int % 58
digit_char = alphabet[digit]
b58_string = digit_char + b58_string
address_int //= 58
ones = leading_zeros // 2
for one in range(ones):
b58_string = '1' + b58_string
return b58_string
I then use a few lines of code to get this working, using the example private key from the above guide, as follows:
key = ‘0C28FCA386C7A227600B2FE50B7CAE11EC86D3BF1FBE471BE89827E19D72AA1D‘
address = wif.private_to_wif(key)
Print(address)
I should be getting the output: 5HueCGU8rMjxEXxiPuD5BDku4MkFqeZyd4dZ1jvhTVqvbTLvyTJ
Instead I’m getting:
5HueCGU8rMjxEXxiPuD5BDku4MkFqeZyd4dZ1jvhTVqvbWs6eYX
It’s only the last 6 characters that differ!
Any suggestions and help would be greatly appreciated.
Thank you in advance.
Connor
I have managed to find the solution by adding a missing encoding step.
I am posting for all those who run into a similar issue and can see the steps that brought resolution.
def create_wif_address(extended_key):
extended_key_dec = codecs.decode(extended_key, 'hex')
first_hash = hashlib.sha256(extended_key_dec)
first_digest = first_hash.digest()
second_hash = hashlib.sha256(first_digest)
second_digest = second_hash.digest()
second_digest_hex = codecs.encode(second_digest, 'hex')
checksum = second_digest_hex[:8]
extended_key_chksm = (extended_key + checksum).decode('utf-8')
wif_address = base58(extended_key_chksm)
return wif_address
So above I added in a step to the function, at the beginning, to decode the passed in variable from a hexadecimal byte string to raw bytes, which is what the hashing algorithms require it seems, and this produced the result I was hoping to achieve.
Connor
I want to check hospitals near me, but I get OVER_QUERY_LIMIT error. The fact is that the key is new and didn`t use before. What can be the problem?
#app.route('/hospitals', methods=['GET','POST'])
def hospitals():
g = geocoder.ip('me')
lt_lg = g.latlng
lt = lt_lg[0]
lg = lt_lg[1]
API_KEY = 'mykey'
google_places = GooglePlaces(API_KEY)
query_result = google_places.nearby_search(
lat_lng ={'lat': lt, 'lng': lg},
radius = 5000,
types =[types.TYPE_HOSPITAL])
if query_result.has_attributions:
print (query_result.html_attributions)
for place in query_result.places:
print("Latitude", place.geo_location['lat'])
print("Longitude", place.geo_location['lng'])
return render_template('hospitals.html', places=query_result.places)
I am trying to create a dashboard of data for our university, and have run into a problem with how it is presenting. I am using Bokeh and Python to create somewhat interactive graphs. My checkbox group is not updating when I click a box to select the college for the major. I have tried changing several items, but cannot figure out what I am doing wrong.
My code:
# Available college list
available_colleges = list(df['College'].unique())
source_maj = ColumnDataSource(df)
grouped_maj = df.groupby('Major').sum()
source_maj = ColumnDataSource(grouped_maj)
major = source_maj.data['Major'].tolist()
p_maj = figure(x_range=major, width=1100, height=500)
p_maj.xaxis.major_label_orientation = math.pi/4
color_map = factor_cmap(field_name='Major',
palette=Magma11, factors=level)
p_maj.vbar(x='Major', top='AY2018_19', source=source_maj, width=0.2, color=color_map)
p_maj.title.text ='Enrollment by Major'
p_maj.xaxis.axis_label = 'Major'
p_maj.yaxis.axis_label = 'Enrolled Students'
hover = HoverTool()
hover.tooltips = [
("2019-2020", "#AY2019_20"),
("2018-2019", "#AY2018_19"),
("2017-2018", "#AY2017_18")]
hover.mode = 'vline'
callback = CustomJS(args=dict(source=source_maj), code="""
const labels = cb_obj.labels;
const active = cb_obj.active;
const data = source_maj.data;
const sourceLen = data.combined.length;
const combined = Array(sourceLen).fill(undefined);
if (active.length > 0) {
const selectedColumns = labels.filter((val, ind) => active.includes(ind));
for(let i = 0; i < sourceLen; i++) {
let sum = 0;
for(col of selectedColumns){
sum += Major[col][i];
}
combined[i] = sum;
}
}
Major.combined=combined;
source_maj.change.emit();
""")
colleges_selection = CheckboxGroup(labels=available_colleges, active = [0], callback=callback)
controls = WidgetBox(colleges_selection)
p_maj = row(controls, p_maj)
Data is formated in a csv sheet that is being read
What it looks like, but nothing updates
Any help is greatly appreciated.
You'll probably want to watch the output the browser sends to the javascript console; it'll tell you what's going wrong here.
A couple places to start: your arguments to the CustomJS object bring in the python object 'source_maj' and rename it as 'source', but then in your JS code you refer to it as 'source_maj'. Also, your JS code makes reference to 'Major', but this isn't an object that the JS knows about (i.e. it wasn't brought in with the args).
So I get this list back from interactive brokers. (API 9.73 using this repo)
ib = IB()
ib.connect('127.0.0.1', 7497, clientId=2)
data = ib.positions()
print((data))
print(type(data))
The data comes back as , but here is the response.
`[Position(account='DUC00074', contract=Contract(conId=43645865, symbol='IBKR', secType='STK', exchange='NASDAQ', currency='USD', localSymbol='IBKR', tradingClass='NMS'), position=2800.0, avgCost=39.4058383), Position(account='DUC00074', contract=Contract(conId=72063691, symbol='BRK B', secType='STK',exchange='NYSE', currency='USD', localSymbol='BRK B', tradingClass='BRK B'), position=250.0, avgCost=163.4365424)]`
I have got this far:
for d in data:
for i in d:
print(i)
But I have no idea as to how I would parse and then dump into a DB, anything after Position(... So to be really clear, I don't know how I would parse, like I would say in php / json.
Okay, Im new to python, not new to programing. So the response from Interactive Brokers threw me off. I'm so used to JSON response. Regardless, what it comes down to is this is a list of objects, (the example above). That might be simple, but missed it. Once I figured it out it became a little easier.
Here is the final code, hopefully this will help someone else down the line.
for obj in data:
#the line below just bascially dumps the object
print("obj={} ".format(obj))
#looking for account number
#"contract" is an object inside an object, so I had to extract that.
if(getattr(obj, 'account') == '123456'):
print("x={} ".format(getattr(obj, 'account')))
account = (getattr(obj, 'account'))
contract = getattr(obj, 'contract')
contractId = getattr(contract, 'conId')
symbol = getattr(contract, 'symbol')
secType = getattr(contract, 'secType')
exdate = getattr(contract, 'lastTradeDateOrContractMonth')
strike = getattr(contract, 'strike')
opt_type = getattr(contract, 'right')
localSymbol = getattr(contract, 'localSymbol')
position = getattr(obj, 'position')
avgCost = getattr(obj, 'avgCost')
sql = "insert into IB_opt (account, contractId, symbol, secType, exdate, opt_type, localSymbol, position, avgCost,strike) values (%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)";
args = (account, contractId, symbol, secType, exdate, opt_type, localSymbol, position, avgCost,strike)
cursor.execute(sql, args)
Of all the sites I looked at this one was pretty helpful.