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I am a newbie in data analysis stuff. I am trying to analyse a dataset using python. enter image description here

  1. I want to count no. of 1s in survived column
  2. No. of male , female in Sex column

PassengerId Survived Pclass Sex
0 1 0 3 male 1 2 1 1 female 2 3 1 3 male 3 4 1 1 female 4 5 0 3 male

I tried groupby() but its giving error.

In[88] titanic_data.groupby('Survived') Out[88] <pandas.core.groupby.DataFrameGroupBy object at 0x000000000BFFE588>

Please suggest solution

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    Can you show your efforts, also the norm is to provide raw data rather than an image of your data. Commented Jul 28, 2016 at 7:44
  • Thanks for suggesting me to paste raw data. I have posted it. Commented Jul 28, 2016 at 7:56
  • To clarify, it isn't giving an error. It is printing an object reference rather than a human-readable format for the table (because of the grouping). Edit submitted. Commented Aug 16, 2018 at 14:20

1 Answer 1

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use value_counts:

df['Survived'].value_counts()
df['Sex'].value_counts()
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3 Comments

1 problem per question, incrementing your requirements is poor form, SO is not a forum
@EdChum thanks for your suggestion
This counts total number of male and female but how about number of females in pclass1 and number of males in pclass2 etc?

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