Python Pandas NameError：未定义名称“数据”
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Python Pandas NameError: name 'data' is not defined
提问by Jerry Fanelli
I'm new to coding. When I attempt to run this it says:
我是编码新手。当我尝试运行它时，它说：
NameError: name 'data' is not defined.
NameError：未定义名称“数据”。
import numpy as np
import pandas as pd
from scipy import stats
from matplotlib import pyplot as plt
from matplotlib.ticker import MaxNLocator
import datetime
import json
from bs4 import BeautifulSoup
import requests
import time
def fetchCryptoClose(fsym, tsym):
# function fetches the close-price time-series from cryptocompare.com
# it may ignore USDT coin (due to near-zero pricing)
# daily sampled
cols = ['date', 'timestamp', fsym]
lst = ['time', 'open', 'high', 'low', 'close']
timestamp_today = datetime.today().timestamp()
curr_timestamp = timestamp_today
for j in range(2):
df = pd.DataFrame(columns=cols)
url = "https://min-api.cryptocompare.com/data/histoday?fsym=" + fsym + \
"&tsym=" + tsym + "&toTs=" + str(int(curr_timestamp)) + "&limit=3"
response = requests.get(url)
soup = BeautifulSoup(response.content, "html.parser")
dic = json.loads(soup.prettify())
for i in range(1, 4):
tmp = []
for e in enumerate(lst):
x = e[0]
y = dic['Data'][i][e[1]]
if(x == 0):
tmp.append(str(timestamp2date(y)))
tmp.append(y)
if(np.sum(tmp[-4::]) > 0): # remove for USDT
tmp = np.array(tmp)
tmp = tmp[[0,1,4]] # filter solely for close prices
df.loc[len(df)] = np.array(tmp)
# ensure a correct date format
df.index = pd.to_datetime(df.date, format="%Y-%m-%d")
df.drop('date', axis=1, inplace=True)
curr_timestamp = int(df.ix[0][0])
if(j == 0):
df0 = df.copy()
else:
data = pd.concat([df, df0], axis=0)
data.drop("timestamp", axis=1, inplace=True)
return data # DataFrame
# N-Cryptocurrency Portfolio (tickers)
fsym = ['BTC', 'ETH', 'XRP', 'LTC', 'DASH', 'XMR', 'ETC', 'MAID', 'XEM', 'REP']
# vs.
tsym = 'USD'
for e in enumerate(fsym):
print(e[0], e[1])
if(e[0] == 0):
try:
data = fetchCryptoClose(e[1], tsym)
except:
pass
else:
try:
data = data.join(fetchCryptoClose(e[1], tsym))
except:
pass
# ensure values to be floats
# save portfolio to a file (HDF5 file format)
store = pd.HDFStore('portfolio2.h5')
store['data'] = data
store.close()
# read in your portfolio from a file
df = pd.read_hdf('portfolio2.h5', 'data')
print(df)
回答by Mike Müller
Don't use try-except-passbecause will silence all your exceptions and you might never actually create `data.
不要使用try- except-pass因为会使您的所有异常静音并且您可能永远不会真正创建 `data.
Replace this code:
替换此代码：
for e in enumerate(fsym):
print(e[0], e[1])
if(e[0] == 0):
try:
data = fetchCryptoClose(e[1], tsym)
except:
pass
else:
try:
data = data.join(fetchCryptoClose(e[1], tsym))
except:
pass
with this:
有了这个：
for e in enumerate(fsym):
print(e[0], e[1])
if(e[0] == 0):
data = fetchCryptoClose(e[1], tsym)
else:
data = data.join(fetchCryptoClose(e[1], tsym))
and see where your real exceptions are.
看看你真正的例外在哪里。
