Pandas:将dataframe附加到另一个d

Question

附加数据帧时出现问题。 我试着执行这段代码

df_all = pd.read_csv('data.csv', error_bad_lines=False, chunksize=1000000)
urls = pd.read_excel('url_june.xlsx')
substr = urls.url.values.tolist()
df_res = pd.DataFrame()
for df in df_all:
    for i in substr:
        res = df[df['url'].str.contains(i)]
        df_res.append(res)

当我试图保存df_res时，会得到空的数据帧。 df_all看起来像

ID,"url","used_at","active_seconds"
b20f9412f914ad83b6611d69dbe3b2b4,"mobiguru.ru/phones/apple/comp/32gb/apple_iphone_5s.html",2015-10-01 00:00:25,1
b20f9412f914ad83b6611d69dbe3b2b4,"mobiguru.ru/phones/apple/comp/32gb/apple_iphone_5s.html",2015-10-01 00:00:31,30
f85ce4b2f8787d48edc8612b2ccaca83,"4pda.ru/forum/index.php?showtopic=634566&view=getnewpost",2015-10-01 00:01:49,2
d3b0ef7d85dbb4dbb75e8a5950bad225,"shop.mts.ru/smartfony/mts/smartfon-smart-sprint-4g-sim-lock-white.html?utm_source=admitad&utm_medium=cpa&utm_content=300&utm_campaign=gde_cpa&uid=3",2015-10-01 00:03:19,34
078d388438ebf1d4142808f58fb66c87,"market.yandex.ru/product/12675734/spec?hid=91491&track=char",2015-10-01 00:03:48,2
d3b0ef7d85dbb4dbb75e8a5950bad225,"avito.ru/yoshkar-ola/telefony/mts",2015-10-01 00:04:21,4
d3b0ef7d85dbb4dbb75e8a5950bad225,"shoppingcart.aliexpress.com/order/confirm_order",2015-10-01 00:04:25,1
d3b0ef7d85dbb4dbb75e8a5950bad225,"shoppingcart.aliexpress.com/order/confirm_order",2015-10-01 00:04:26,9

而urls看起来

url
shoppingcart.aliexpress.com/order/confirm_order
ozon.ru/?context=order_done&number=
lk.wildberries.ru/basket/orderconfirmed
lamoda.ru/checkout/onepage/success/quick
mvideo.ru/confirmation?_requestid=
eldorado.ru/personal/order.php?step=confirm

当我在循环中打印res时，它不会为空。但是当我尝试在追加后的循环df_res中打印时，它返回空数据帧。 我找不到我的错误。我怎样才能修好它？

Answer 1

如果要基于索引追加：

df_res = pd.DataFrame(data = None, columns= df.columns)

all_res = []

d1 = df.ix[index-10:index-1,]     #it will take 10 rows before i-th index

all_res.append(d1)

df_res = pd.concat(all_res)

Answer 2

如果你看the documentation for ^{}

Append rows of other to the end of this frame, returning a new object. Columns not in this frame are added as new columns.

（强调我的）。

试试看

df_res = df_res.append(res)

---

顺便说一下，请注意pandas对于通过连续连接创建数据帧没有那么有效。你可以试试这个，而不是：

all_res = []
for df in df_all:
    for i in substr:
        res = df[df['url'].str.contains(i)]
        all_res.append(res)

df_res = pd.concat(all_res)

这首先创建所有部分的列表，然后在最后从所有部分创建一个数据帧。