import pandas

sub_info = pandas.read_csv("contract.csv")

#sub_info

#print (sub_info)

type(sub_info)

#print (sub_info.dtypes)

first_rows = sub_info.head(1)

#print (first_rows)

#print (sub_info.columns)

#print (sub_info.shape)

#print (sub_info.loc[1])

sub_info.loc[0:3]

two_five_nine = [2,5,9]

sub_info.loc[two_five_nine]

id1 = sub_info["CONTRACTID"]

id1

str1 = ["CONTRACTID","STATUS"]

id2 = sub_info[str1]

id2

sub_info.columns

columns_list = sub_info.columns.tolist()

time_list = []

for i in columns_list:

    if i.endswith("TIME"):

        time_list.append(i)

time_info = sub_info[time_list]

is_value_empty = time_info.isnull()

is_value_empty

time_info.fillna("0")

#用前一个数据代替NaN：method='pad'

time_info.fillna(method='pad')

#与pad相反，bfill表示用后一个数据代替NaN

time_info.fillna(method='bfill')

#用limit限制每列可以替代NaN的数目

time_info.fillna(method='bfill',limit=1)

#使用平均数代替NaN

time_info.fillna(time_info.mean())

#指定列 数据代替NaN

time_info.fillna(time_info.mean()['SUBTIME':'OPRTIME'])

test_info = sub_info[["CONTRACTID","STATUS"]]

#A value is trying to be set on a copy of a slice from a DataFrame

test_num = test_info["STATUS"] / 10

test_info["test"] = test_num

test_info

test_num = sub_info["STATUS"] / 10

sub_info["test"] = test_num

sub_info

CONTRACTID_MAX = sub_info["CONTRACTID"].max()

max_percent = sub_info["CONTRACTID"] / CONTRACTID_MAX

sub_info["max_percent"] = max_percent

#对列排序，参数True 表示不产生拷贝，直接在原矩阵操作 

sub_info.sort_values("CONTRACTID",inplace=True)

sub_info

#ascending 降序

sub_info.sort_values("CONTRACTID",inplace=True,ascending=False)

sub_info