There are various data wrangling methods. Have you tried to use any of them for dataframe or series?
So this is the recipe on how we can utilise a Pandas dataframe & series for data wrangling.
import pandas as pd
We have only imported pandas which is needed.
We have created a series of numbers in the boject floodingReports and then added index to each number.
floodingReports = pd.Series([5, 6, 2, 9, 12])
print(floodingReports)
floodingReports = pd.Series([5, 6, 2, 9, 12], index=["Cochise County", "Pima County",
"Santa Cruz County", "Maricopa County", "Yuma County"])
print(floodingReports)
First we have printed the number as per the index. Then we have printed the index on a condition that the value should be greater than 6.
print(floodingReports["Cochise County"])
print(floodingReports[floodingReports > 6])
We have created a series from a dictionary by passing the dictionary through pd.series.
fireReports_dict = {"Cochise County": 12, "Pima County": 342,
"Santa Cruz County": 13, "Maricopa County": 42,
"Yuma County" : 52}
fireReports = pd.Series(fireReports_dict)
print(fireReports)
We can change the index of series by defining new set of index in series.index function.
fireReports.index = ["Cochice", "Pima", "Santa Cruz", "Maricopa", "Yuma"]
We have created a dataframe from a dictionary by passing the dictionary through pd.DataFrame
data = {"county": ["Cochice", "Pima", "Santa Cruz", "Maricopa", "Yuma"],
"year": [2012, 2012, 2013, 2014, 2014],
"reports": [4, 24, 31, 2, 3]}
df = pd.DataFrame(data)
print(df)
We are peroforming three Wrangling for better understanding.
dfColumnOrdered["newsCoverage"] = pd.Series([42.3, 92.1, 12.2, 39.3, 30.2])
print(dfColumnOrdered)
del dfColumnOrdered["newsCoverage"]
print(dfColumnOrdered)
# Transpose the dataframe
print(dfColumnOrdered.T)
0 5 1 6 2 2 3 9 4 12 dtype: int64 Cochise County 5 Pima County 6 Santa Cruz County 2 Maricopa County 9 Yuma County 12 dtype: int64 5 Maricopa County 9 Yuma County 12 dtype: int64 Cochise County 12 Pima County 342 Santa Cruz County 13 Maricopa County 42 Yuma County 52 dtype: int64 county year reports 0 Cochice 2012 4 1 Pima 2012 24 2 Santa Cruz 2013 31 3 Maricopa 2014 2 4 Yuma 2014 3 county year reports newsCoverage 0 Cochice 2012 4 42.3 1 Pima 2012 24 92.1 2 Santa Cruz 2013 31 12.2 3 Maricopa 2014 2 39.3 4 Yuma 2014 3 30.2 county year reports 0 Cochice 2012 4 1 Pima 2012 24 2 Santa Cruz 2013 31 3 Maricopa 2014 2 4 Yuma 2014 3 0 1 2 3 4 county Cochice Pima Santa Cruz Maricopa Yuma year 2012 2012 2013 2014 2014 reports 4 24 31 2 3