Question

Exercise 2: Summarize the data Get some quick stats with the describe() method. - In [6]: # Your code here Out[6] salary yrs since.phd yrs.service 399.000000 399.000000 count 400.000000 22.233083 12.909360 17.601504 113538 660000 12.987009 30253.387593 0.000000 57800.000000 7.000000 91000.000000 1.000000 25% 12 000000 50% 21.000000 16.000000 107175.000000 75% 32.000000 56 000000 26.500000 134046250000 60.000000 231545 000000 ma describe only gives you stats for quantitative values Let's find out how many observations we have for the rank and sex variables. First use the value_counts() method to get the count of each unique value in the rank column Examples here los leone.comic (documentation here and and docendanda In 171 mur rode here!

Answer 1

#import the library
import pandas as pd

#read the csv file using pandas
df = pd.read_csv("Salaries.csv")

#summarise the data
df.describe()

#number of labels and observations in variable rank
df["rank"].value_counts()

#number of labels and observations in variable sex
df["sex"].value_counts()

Activities Firefox Web Browser Thu 07:02 2 Salaries - Jupyter Notebook - Mozilla Firefox Downloads/ Salaries - Jupyter Noteb X New Tab x + D o localhost:8888/notebooks/Downloads/Salaries.ipynb lu EN jupyter Salaries Last Checkpoint: 5 minutes ago (unsaved changes) Logout File Edit View Insert Cell Kernel Widgets Help Trusted Python 30 + Run с Code In [1]: #import the library import pandas as pd In [2] : #read the csv file using pandas df = pd. read_csv ("Salaries.csv") In [12] : #summarise the data df.describe() Out[12] : yrs.since.phd yrs.service count 397.000000 397.000000 salary 397.000000 mean 22.314861 17.614610 113706.458438 std 12.887003 13.006024 30289.038695 min 1.000000 0.000000 57800.000000 25% 12.000000 7.000000 91000.000000 5096 21.000000 16.000000 107300.000000 7596 32.000000 27.000000 134185.000000 max 56.000000 60.000000 231545.000000 In [13]: #number of labels and observations in variable rank df["rank"].value_counts() Out[13] : Prof 266 AsstProf 67

Activities Firefox Web Browser Thu 07:02 2 Salaries - Jupyter Notebook - Mozilla Firefox Downloads/ Salaries - Jupyter Noteb X New Tab x + D o localhost:8888/notebooks/Downloads/Salaries.ipynb EN jupyter Salaries Last Checkpoint: 6 minutes ago (unsaved changes) Logout File Edit View Insert Cell Kernel Widgets Help Trusted Python 3 O + Run e Code std 12.887003 13.006024 30289.038695 min 1.000000 0.000000 57800.000000 25% 12.000000 7.000000 91000.000000 50% 21.000000 16.000000 107300.000000 7596 32.000000 27.000000 134185.000000 max 56.000000 60.000000 231545.000000 In [13]: #number of labels and observations in variable rank df ["rank"].value_counts() Out[13]: Prof 266 AsstProf 67 AssocProf 64 Name: rank, dtype: int64 In [14] : #number of labels and observations in variable sex df["sex"].value_counts() Out[14]: Male 358 Female 39 Name: sex, dtype: int64 In [ ]:

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