Was bedeutet "...:" in der Ipython-Konsole Anakonda?

Question

Ich versuche, einen Datenrahmen in einem CSV direkt von Ipython Console zu drucken, aber ich bekomme dieses Symbol und dann nichts "...:". Was bedeutet das Symbol?

Gibt es trotzdem ich kann meine csv zum Drucken zwingen?

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

Anzeige Sizing

Wenn pandas in ipython/Jupyter an die Konsole Druck wird, verwendet er ... zu zeigen, dass es Daten in-zwischen den Reihen der angezeigten Daten auf die Ausgabe. Dies ist nützlich, wenn die Daten zu groß sind, um jeden einzelnen Wert zu drucken. Dies ist das Standardverhalten, es sei denn, Sie überschreiben die Anzeigeoptionen.

Von 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]