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%matplotlib inline
import numpy
import pandas
import matplotlib.pyplot as plt
import seaborn as sns
import re
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accounting_neeq = pandas.read_csv("../data/NEEQAccountingData.csv", parse_dates=[2, 6, 29, 30])
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items = ["资产总计", "营业收入", "归属母公司股东的净利润", "经营活动产生的现金流量净额", "固定资产"]
index_drops = accounting_neeq[accounting_neeq[items].isnull().all(axis=1)].index
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accounting_neeq.loc[index_drops, :].to_csv("../data/accountingtmp.csv", index=False)
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accounting_neeq.loc[accounting_neeq["relativeYear"] == 0, "挂牌前后"] = "挂牌后"
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accounting_group = accounting_neeq.groupby(["证券代码"])
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x = accounting_neeq[accounting_neeq["证券代码"] == "430699.OC"]
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def relative_years_correction(data):
year = data.loc[data["relativeYear"] == 0, "年度"]
if len(year) != 0:
relativeYears = numpy.array(data.loc[:, "年度"] - int(year))
else:
year = data.loc[data["relativeYear"] == -1, "年度"]
relativeYears = numpy.array(data.loc[:, "年度"] - int(year) - 1)
data.loc[:, "relativeYear"] = relativeYears
return data
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accounting_neeq = accounting_group.apply(relative_years_correction)
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accounting_neeq.to_csv("../data/NEEQAccountingData.csv", index=False)
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accounting_neeq = pandas.read_csv("../data/NEEQAccountingData.csv", parse_dates=[2, 6, 29, 30])
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TooManyYears = ["832715.OC", "834019.OC"]
RevenueOnly = ["833318.OC", "834178.OC", "834906.OC", "835024.OC", "835433.OC", "834090.OC", "835919.OC", ]
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