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

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

## Pandas Datetime: Exercise-22 with Solution

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

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
hour_v_year = df.pivot_table(columns=df['Date_time'].dt.hour,index=df['Date_time'].dt.year.apply(is_top_years),aggfunc='count',values='city')
hour_v_year.columns = hour_v_year.columns.astype(int)
hour_v_year.columns = hour_v_year.columns.astype(str) + ":00"
hour_v_year.index = hour_v_year.index.astype(int)
print("\nComparison of the top 10 years in which the UFO was sighted vs the hours of the day:")
``````

Sample Output:

```Comparison of the top 10 years in which the UFO was sighted vs the hours of the day:
0:00  1:00  2:00  4:00  ...    20:00  21:00  22:00  23:00
Date_time                          ...
1993        1.0   1.0   1.0   NaN  ...      2.0    NaN    NaN    4.0
1994        NaN   NaN   NaN   NaN  ...      NaN    4.0    2.0    1.0
1995        NaN   NaN   1.0   1.0  ...      2.0    1.0    1.0    3.0
1996        NaN   1.0   NaN   NaN  ...      1.0    NaN    2.0    1.0
1997        NaN   1.0   NaN   1.0  ...      NaN    4.0    1.0    2.0
1998        2.0   1.0   NaN   NaN  ...      2.0    2.0    2.0    NaN
1999        2.0   NaN   1.0   NaN  ...      NaN    2.0    1.0    2.0
2000        NaN   NaN   1.0   NaN  ...      4.0    2.0    2.0    1.0
2001        3.0   1.0   NaN   1.0  ...      1.0    5.0    NaN    NaN
2002        NaN   1.0   NaN   NaN  ...      2.0    NaN    NaN    3.0

[10 rows x 20 columns]
```

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
```