在Ipython控制台anaconda中，“…：”是什么意思？

Question

I am trying to print a dataframe into a csv directly from Ipython Console, but I get this symbol and then nothing " ...:". What does the symbol mean?

Is there anyway I can force my csv to print ?

Code:

import ET_Client
import pandas as pd


AggreateDF = pd.DataFrame()

try:

    debug = False
    stubObj = ET_Client.ET_Client(False, debug)

    print '>>>BounceEvents'
    getBounceEvent = ET_Client.ET_BounceEvent()
    getBounceEvent.auth_stub = stubObj    
    getResponse1 = getBounceEvent.get()
    ResponseResultsBounces = getResponse1.results
    Results_Message = getResponse1.message
    print "This is orginial " + str(Results_Message) 
    #print ResponseResultsBounces

    i = 1
    while (Results_Message == 'MoreDataAvailable'):
        if i > 5: break
        print Results_Message
        results1 = getResponse1.results
        i = i + 1
        ClientIDBounces = []
        partner_keys1 = []
        created_dates1 = []
        modified_date1 = []
        ID1 = []
        ObjectID1 = []
        SendID1 = []
        SubscriberKey1 = []
        EventDate1 = []
        EventType1 = []
        TriggeredSendDefinitionObjectID1 = []
        BatchID1 = []
        SMTPCode = []
        BounceCategory = []
        SMTPReason = []
        BounceType = []

        for BounceEvent in ResponseResultsBounces:
            ClientIDBounces.append(str(BounceEvent['Client']['ID']))
            partner_keys1.append(BounceEvent['PartnerKey'])
            created_dates1.append(BounceEvent['CreatedDate'])
            modified_date1.append(BounceEvent['ModifiedDate'])
            ID1.append(BounceEvent['ID'])
            ObjectID1.append(BounceEvent['ObjectID'])
            SendID1.append(BounceEvent['SendID'])
            SubscriberKey1.append(BounceEvent['SubscriberKey'])
            EventDate1.append(BounceEvent['EventDate'])
            EventType1.append(BounceEvent['EventType'])
            TriggeredSendDefinitionObjectID1.append(BounceEvent['TriggeredSendDefinitionObjectID'])
            BatchID1.append(BounceEvent['BatchID'])
            SMTPCode.append(BounceEvent['SMTPCode'])
            BounceCategory.append(BounceEvent['BounceCategory'])
            SMTPReason.append(BounceEvent['SMTPReason'])
            BounceType.append(BounceEvent['BounceType'])

        df1 = pd.DataFrame({'ClientID': ClientIDBounces, 'PartnerKey': partner_keys1,
                       'CreatedDate' : created_dates1, 'ModifiedDate': modified_date1, 
                       'ID':ID1, 'ObjectID': ObjectID1,'SendID':SendID1,'SubscriberKey':SubscriberKey1,
                       'EventDate':EventDate1,'EventType':EventType1,'TriggeredSendDefinitionObjectID':TriggeredSendDefinitionObjectID1,
                       'BatchID':BatchID1,'SMTPCode':SMTPCode,'BounceCategory':BounceCategory,'SMTPReason':SMTPReason,'BounceType':BounceType})
        #print(df1['ID'].max())
        AggreateDF = AggreateDF.append(df1)   
        print(AggreateDF)          
        #print df1
        df_masked1 = df1[(df1.EventDate > "2016-02-20") & (df1.EventDate < "2016-07-25")]

Answer 1

Display Sizing

When pandas is printing to the console in iPython/Jupyter, it uses ... to show that there is data in-between rows of the data displayed on the output. This is useful when the data is to large to print every single value. This is the default behavior unless you override the display options.

From Frequently Used Options

 df = pd.DataFrame(np.random.randn(7,2))
 pd.set_option('max_rows', 7)
 df

---

          0         1
0  0.469112 -0.282863
1 -1.509059 -1.135632
2  1.212112 -0.173215
3  0.119209 -1.044236
4 -0.861849 -2.104569
5 -0.494929  1.071804
6  0.721555 -0.706771

---

pd.set_option('max_rows', 5)
df

---

           0         1
0   0.469112 -0.282863
1  -1.509059 -1.135632
..       ...       ...
5  -0.494929  1.071804
6   0.721555 -0.706771

[7 rows x 2 columns]