# $0.$ import libraries

import pandas as pd

import numpy as np

import matplotlib.pylab as plt

import seaborn as sns

# $1.$ load the data set

#

# $2.$ show data dimensions

#

$(1364,41)$

# $3.$ show column names.

#

Index$([\text{'}$country$\text{'},$ 'location$\_$name', 'latitu de$\text{'},$ 'longitude', 'timezone',

'last$\_$updated$\_$epoch', 'last$\_$update d$\text{'},$ 'temperature$\_$celsius' $,$

'temperature$\_$fahrenheit', 'conditio n$\_$text', 'wind$\_$mph$\text{'},$ 'wind$\_$kph$\text{'},$

'wind$\_$degree', 'wind$\_$direction', $\text{'}$p ressure$\_$mb$\text{'},$ 'pressure$\_$in$\text{'},$

'precip$\_$mm$\text{'},$ 'precip$\_$in$\text{'},$ 'humidit y$\text{'},$ 'cloud', 'feels$\_$like$\_$celsius', 'feels$\_$like$\_$fahrenheit', 'visibilit y$\_$km$\text{'},$ 'visibility$\_$miles',

$\text{'}$uv$\_$index', 'gust$\_$mph$\text{'},$ 'gust$\_$kph$\text{'},$ 'air$\_$quality$\_$Carbon$\_$Monoxide' $,$

'air$\_$quality$\_$ozone' $,$ 'air$\_$quality$\_$N itrogen$\_$dioxide' $,$ 'air$\_$quality$\_$Sulphur$\_$dioxide', 'air $\_$quality$\_$PM$2\mathrm{.}5\text{'},$ 'air$\_$quality$\_$PM$10\text{'},$

'air$\_$quality$\_$us$-$epa$-$index', 'air$\_$qu ality$\_$gb$-$defra$-$index' $,$ 'sunrise',

'sunset', 'moonrise', 'moonset', $\text{'}$m oon$\_$phase', 'moon$\_$illumination'$],$ dtype$=$'object $\text{'})$

# $4.$ show columns data types

#