text 熊猫 - 重命名列
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import pandas as pd
ufo = pd.read_csv('http://bit.ly/uforeports')
ufo.columns
# Index(['City', 'Colors Reported', 'Shape Reported', 'State', 'Time'], dtype='object')
ufo.rename(columns={'Colors Reported': 'Colors_Reported',
'Shape Reported': 'Shape_Reported'}, inplace=True)
# Index(['City', 'Colors_Reported', 'Shape_Reported', 'State', 'Time'], dtype='object')
# OR
ufo_cols = ['city', 'colors reported', 'shape reported', 'state', 'time']
ufo.columns = ufo_cols
# Index(['city', 'colors reported', 'shape reported', 'state', 'time'], dtype='object')
# OR
ufo = pd.read_csv('http://bit.ly/uforeports',
names=ufo_cols, # Passing a list of columns names as parameter.
header=0) # Set to 0 if csv or tsv has a header by default.
ufo.columns = ufo.columns.str.replace(' ', '_')
# Index(['city', 'colors_reported', 'shape_reported', 'state', 'time'], dtype='object'){
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"ufo = pd.read_csv('http://bit.ly/uforeports')"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>City</th>\n",
" <th>Colors Reported</th>\n",
" <th>Shape Reported</th>\n",
" <th>State</th>\n",
" <th>Time</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Ithaca</td>\n",
" <td>NaN</td>\n",
" <td>TRIANGLE</td>\n",
" <td>NY</td>\n",
" <td>6/1/1930 22:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Willingboro</td>\n",
" <td>NaN</td>\n",
" <td>OTHER</td>\n",
" <td>NJ</td>\n",
" <td>6/30/1930 20:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Holyoke</td>\n",
" <td>NaN</td>\n",
" <td>OVAL</td>\n",
" <td>CO</td>\n",
" <td>2/15/1931 14:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Abilene</td>\n",
" <td>NaN</td>\n",
" <td>DISK</td>\n",
" <td>KS</td>\n",
" <td>6/1/1931 13:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>New York Worlds Fair</td>\n",
" <td>NaN</td>\n",
" <td>LIGHT</td>\n",
" <td>NY</td>\n",
" <td>4/18/1933 19:00</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" City Colors Reported Shape Reported State Time\n",
"0 Ithaca NaN TRIANGLE NY 6/1/1930 22:00\n",
"1 Willingboro NaN OTHER NJ 6/30/1930 20:00\n",
"2 Holyoke NaN OVAL CO 2/15/1931 14:00\n",
"3 Abilene NaN DISK KS 6/1/1931 13:00\n",
"4 New York Worlds Fair NaN LIGHT NY 4/18/1933 19:00"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ufo.head()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['City', 'Colors Reported', 'Shape Reported', 'State', 'Time'], dtype='object')"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ufo.columns"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"ufo_cols = ['city', 'colors reported', 'shape reported', 'state', 'time']"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"ufo.columns = ufo_cols"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>city</th>\n",
" <th>colors reported</th>\n",
" <th>shape reported</th>\n",
" <th>state</th>\n",
" <th>time</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Ithaca</td>\n",
" <td>NaN</td>\n",
" <td>TRIANGLE</td>\n",
" <td>NY</td>\n",
" <td>6/1/1930 22:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Willingboro</td>\n",
" <td>NaN</td>\n",
" <td>OTHER</td>\n",
" <td>NJ</td>\n",
" <td>6/30/1930 20:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Holyoke</td>\n",
" <td>NaN</td>\n",
" <td>OVAL</td>\n",
" <td>CO</td>\n",
" <td>2/15/1931 14:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Abilene</td>\n",
" <td>NaN</td>\n",
" <td>DISK</td>\n",
" <td>KS</td>\n",
" <td>6/1/1931 13:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>New York Worlds Fair</td>\n",
" <td>NaN</td>\n",
" <td>LIGHT</td>\n",
" <td>NY</td>\n",
" <td>4/18/1933 19:00</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" city colors reported shape reported state time\n",
"0 Ithaca NaN TRIANGLE NY 6/1/1930 22:00\n",
"1 Willingboro NaN OTHER NJ 6/30/1930 20:00\n",
"2 Holyoke NaN OVAL CO 2/15/1931 14:00\n",
"3 Abilene NaN DISK KS 6/1/1931 13:00\n",
"4 New York Worlds Fair NaN LIGHT NY 4/18/1933 19:00"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ufo.head()"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
"ufo = pd.read_csv('http://bit.ly/uforeports', names=ufo_cols, header=0)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>city</th>\n",
" <th>colors reported</th>\n",
" <th>shape reported</th>\n",
" <th>state</th>\n",
" <th>time</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Ithaca</td>\n",
" <td>NaN</td>\n",
" <td>TRIANGLE</td>\n",
" <td>NY</td>\n",
" <td>6/1/1930 22:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Willingboro</td>\n",
" <td>NaN</td>\n",
" <td>OTHER</td>\n",
" <td>NJ</td>\n",
" <td>6/30/1930 20:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Holyoke</td>\n",
" <td>NaN</td>\n",
" <td>OVAL</td>\n",
" <td>CO</td>\n",
" <td>2/15/1931 14:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Abilene</td>\n",
" <td>NaN</td>\n",
" <td>DISK</td>\n",
" <td>KS</td>\n",
" <td>6/1/1931 13:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>New York Worlds Fair</td>\n",
" <td>NaN</td>\n",
" <td>LIGHT</td>\n",
" <td>NY</td>\n",
" <td>4/18/1933 19:00</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" city colors reported shape reported state time\n",
"0 Ithaca NaN TRIANGLE NY 6/1/1930 22:00\n",
"1 Willingboro NaN OTHER NJ 6/30/1930 20:00\n",
"2 Holyoke NaN OVAL CO 2/15/1931 14:00\n",
"3 Abilene NaN DISK KS 6/1/1931 13:00\n",
"4 New York Worlds Fair NaN LIGHT NY 4/18/1933 19:00"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ufo.head()"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"ufo.columns = ufo.columns.str.replace(' ', '_')"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>city</th>\n",
" <th>colors_reported</th>\n",
" <th>shape_reported</th>\n",
" <th>state</th>\n",
" <th>time</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Ithaca</td>\n",
" <td>NaN</td>\n",
" <td>TRIANGLE</td>\n",
" <td>NY</td>\n",
" <td>6/1/1930 22:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Willingboro</td>\n",
" <td>NaN</td>\n",
" <td>OTHER</td>\n",
" <td>NJ</td>\n",
" <td>6/30/1930 20:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Holyoke</td>\n",
" <td>NaN</td>\n",
" <td>OVAL</td>\n",
" <td>CO</td>\n",
" <td>2/15/1931 14:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Abilene</td>\n",
" <td>NaN</td>\n",
" <td>DISK</td>\n",
" <td>KS</td>\n",
" <td>6/1/1931 13:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>New York Worlds Fair</td>\n",
" <td>NaN</td>\n",
" <td>LIGHT</td>\n",
" <td>NY</td>\n",
" <td>4/18/1933 19:00</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" city colors_reported shape_reported state time\n",
"0 Ithaca NaN TRIANGLE NY 6/1/1930 22:00\n",
"1 Willingboro NaN OTHER NJ 6/30/1930 20:00\n",
"2 Holyoke NaN OVAL CO 2/15/1931 14:00\n",
"3 Abilene NaN DISK KS 6/1/1931 13:00\n",
"4 New York Worlds Fair NaN LIGHT NY 4/18/1933 19:00"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ufo.head()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
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"nbformat_minor": 2
}
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