﻿ Pandas Datetime: Create a comparison of the top 10 years in which the UFO was sighted vs each Month - w3resource

# Pandas Datetime: Create a comparison of the top 10 years in which the UFO was sighted vs each Month

## Pandas Datetime: Exercise-23 with Solution

Write a Pandas program to create a comparison of the top 10 years in which the UFO was sighted vs each Month.

Sample Solution:

Python Code:

``````import pandas as pd
#Source: https://bit.ly/1l9yjm9
df['Date_time'] = df['Date_time'].astype('datetime64[ns]')
def is_top_years(year):
if year in most_sightings_years.index:
return year
month_vs_year = df.pivot_table(columns=df['Date_time'].dt.month,index=df['Date_time'].dt.year.apply(is_top_years),aggfunc='count',values='city')
month_vs_year.index = month_vs_year.index.astype(int)
month_vs_year.columns = month_vs_year.columns.astype(int)
print("\nComparison of the top 10 years in which the UFO was sighted vs each month:")
``````

Sample Output:

```Comparison of the top 10 years in which the UFO was sighted vs each month:
Date_time   1    2    3    4    5    6    7    8    9    10   11   12
Date_time
1993       NaN  NaN  1.0  1.0  NaN  1.0  3.0  2.0  3.0  NaN  1.0  NaN
1994       2.0  NaN  3.0  2.0  2.0  NaN  NaN  1.0  NaN  NaN  NaN  1.0
1995       2.0  1.0  NaN  1.0  1.0  1.0  3.0  NaN  1.0  NaN  2.0  NaN
1996       NaN  1.0  NaN  1.0  1.0  1.0  3.0  3.0  1.0  NaN  1.0  NaN
1997       NaN  2.0  1.0  NaN  2.0  1.0  3.0  1.0  1.0  1.0  1.0  1.0
1998       1.0  2.0  1.0  3.0  NaN  2.0  1.0  NaN  NaN  1.0  NaN  2.0
1999       NaN  NaN  2.0  NaN  1.0  2.0  4.0  NaN  NaN  1.0  NaN  1.0
2000       NaN  3.0  2.0  NaN  2.0  1.0  1.0  NaN  NaN  NaN  1.0  2.0
2001       2.0  1.0  2.0  2.0  1.0  2.0  NaN  1.0  2.0  NaN  1.0  1.0
2002       3.0  1.0  1.0  NaN  3.0  NaN  2.0  1.0  2.0  1.0  NaN  NaN
```

Python Code Editor:

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﻿

## Python: Tips of the Day

F strings:

It is a common practice to add variables inside strings. F strings are by far the coolest way of doing it. To appreciate the f strings more, let's first perform the operation with the format function.

```name = 'Owen'
age = 25
print("{} is {} years old".format(name, age))
```

Output:

```Owen is 25 years old
```

We specify the variables that go inside the curly braces by using the format function at the end. F strings allow for specifying the variables inside the string.

```name = 'Owen'
age = 25
print(f"{name} is {age} years old")
```

Output:

```Owen is 25 years old
```

F strings are easier to follow and type. Moreover, they make the code more readable.

```A, B, C = {2, 4, 6}
print(A, B, C)
A, B, C = ['p', 'q', 'r']
print(A, B, C)
```

Output:

```2 4 6
p q r
```