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dsc-0-03-08-understanding-pandas-series-and-dataframes-lab-online-ds-sp-000's Introduction

Understanding Pandas Series and DataFrames - Lab

Introduction

In this lab, let's get some hands on practice working with data cleanup using Pandas.

Objectives

You will be able to:

  • Manipulate columns in DataFrames (df.rename, df.drop)
  • Manipulate the index in DataFrames (df.reindex, df.drop, df.rename)
  • Manipulate column datatypes
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
df = pd.read_csv('turnstile_180901.txt')
print(len(df))
df.head()
197625
<style scoped> .dataframe tbody tr th:only-of-type { vertical-align: middle; }
.dataframe tbody tr th {
    vertical-align: top;
}

.dataframe thead th {
    text-align: right;
}
</style>
C/A UNIT SCP STATION LINENAME DIVISION DATE TIME DESC ENTRIES EXITS
0 A002 R051 02-00-00 59 ST NQR456W BMT 08/25/2018 00:00:00 REGULAR 6736067 2283184
1 A002 R051 02-00-00 59 ST NQR456W BMT 08/25/2018 04:00:00 REGULAR 6736087 2283188
2 A002 R051 02-00-00 59 ST NQR456W BMT 08/25/2018 08:00:00 REGULAR 6736105 2283229
3 A002 R051 02-00-00 59 ST NQR456W BMT 08/25/2018 12:00:00 REGULAR 6736180 2283314
4 A002 R051 02-00-00 59 ST NQR456W BMT 08/25/2018 16:00:00 REGULAR 6736349 2283384

Practice

Objectives

You will be able to:

  • Understand and explain what Pandas Series and DataFrames are and how they differ from dictionaries and lists
  • Create Series & DataFrames from dictionaries and lists
  • Manipulate columns in DataFrames (df.rename, df.drop)
  • Manipulate the index in DataFrames (df.reindex, df.drop, df.rename)
  • Manipulate column datatypes

Rename all the columns to lower case

#Your code here

Change the Index to be the Line Names

#Your code here

Painstakingly change the index back

# Your code here

Create another column 'Num_Lines' that is a count of how many lines pass through a station. Then sort your dataframe by this column in descending order.

# Your code here

Write a function to clean a column name.

def clean(col_name):
    cleaned = #Your code here; whatever you want to do to col_name. Hint: think back to str methods.
    return cleaned
#This is a list comprehension. It applies your clean function to every item in the list.
#We then reassign that to df.columns
#You shouldn't have to change anything here.
#Your function above should work appropriately here.
df.columns = [clean(col) for col in df.columns] 
#Checking the output, we can see the results.
df.columns

Compare subway traffic by day of the week. Display this as a graph.

#Your code here

Is there more subway traffic on a weekend or a weekday? Be specific in comparing magnitudes.

#Your code here

Drop a couple of columns

# Your code here

dsc-0-03-08-understanding-pandas-series-and-dataframes-lab-online-ds-sp-000's People

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